Kaggle NY Taxi trip duration prediction


In [98]:
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
%matplotlib inline

# set Jupyter to display ALL output from a cell (not just last output)
from IPython.core.interactiveshell import InteractiveShell
InteractiveShell.ast_node_interactivity = "all" 

# set pandas and numpy options to make print format nicer
pd.set_option("display.width",100)
pd.set_option("display.max_columns",1000)
pd.set_option('display.max_colwidth', 80)
pd.set_option('display.max_rows', 500)
np.set_printoptions(linewidth=120, threshold=5000, edgeitems=10, suppress=True)

import warnings  # supress annoying seaborn/pandas deprecation warnings
warnings.filterwarnings("ignore", category=DeprecationWarning) 
warnings.filterwarnings("ignore", category=FutureWarning)

Read into dataframes, and add new features


In [128]:
%%time
# create train and test dataframes, with parsed data fields
train = pd.read_csv('train.csv', parse_dates=['pickup_datetime','dropoff_datetime'])
test  = pd.read_csv('test.csv',  parse_dates=['pickup_datetime'])
test_id = test.id.copy() # save test ids for later use in submitting files
print(train.shape, test.shape)


(1458644, 11) (625134, 9)
CPU times: user 5.23 s, sys: 496 ms, total: 5.72 s
Wall time: 5.75 s

In [129]:
%%time
# create new features from location, datetime fields, and others
def great_circle_distance(lat1, long1, lat2, long2):
    EARTH_RADIUS = 6371
    lat1 = np.radians(lat1); lat2 = np.radians(lat2); long1 = np.radians(long1); long2 = np.radians(long2)
    lat_diff  = lat2 - lat1; long_diff = long2 - long1
    temp = np.sin(lat_diff * 0.5) ** 2 + np.cos(lat1) * np.cos(lat2) * np.sin(long_diff * 0.5) ** 2
    return 2 * EARTH_RADIUS * np.arcsin(np.sqrt(temp))

def manhattan_distance(lat1, long1, lat2, long2):
    a = great_circle_distance(lat1, long1, lat1, long2)
    b = great_circle_distance(lat1, long1, lat2, long1)
    return a + b

def bearing(lat1, long1, lat2, long2):
    EARTH_RADIUS = 6371  # in km
    long_diff = np.radians(long2 - long1)
    lat1 = np.radians(lat1); lat2 = np.radians(lat2); long1 = np.radians(long1); long2 = np.radians(long2)
    long_diff = long2 - long1
    y = np.sin(long_diff) * np.cos(lat2)
    x = np.cos(lat1) * np.sin(lat2) - np.sin(lat1) * np.cos(lat2) * np.cos(long_diff)
    return np.degrees(np.arctan2(y, x))

ny_public_holidays = pd.Series([pd.Timestamp('2016-01-01'), pd.Timestamp('2016-01-18'), pd.Timestamp('2016-02-15'),
                                pd.Timestamp('2016-05-30'), pd.Timestamp('2016-07-04'), pd.Timestamp('2016-09-05'),
                                pd.Timestamp('2016-10-10'), pd.Timestamp('2016-11-11'), pd.Timestamp('2016-11-24'),
                                pd.Timestamp('2016-12-26')])

train = train[train.trip_duration < 87000] # remove 4 outliers, more than 1 day
coords = np.vstack((train[['pickup_latitude', 'pickup_longitude']].values,
                    train[['dropoff_latitude', 'dropoff_longitude']].values,
                    test[['pickup_latitude', 'pickup_longitude']].values,
                    test[['dropoff_latitude', 'dropoff_longitude']].values))

from sklearn.decomposition import PCA        # create PCA model of locations to extract max differences
pca = PCA().fit(coords)                      

from sklearn.cluster import MiniBatchKMeans  # create cluster of pickup and dropoff locations
kmeans = MiniBatchKMeans(n_clusters=100, batch_size=10000).fit(coords) # was 100 clusters

# make same new features in both test and train
for data in (train, test):
    data['store_and_fwd_flag']   = data.store_and_fwd_flag.map({'N':0, 'Y':1})
    data['pickup_month_of_year'] = data.pickup_datetime.dt.month
    data['pickup_day_of_week']   = data.pickup_datetime.dt.dayofweek
    data['pickup_day_of_month']  = data.pickup_datetime.dt.day
    data['pickup_day_of_year']   = data.pickup_datetime.dt.dayofyear
    data['pickup_hour_of_day']   = data.pickup_datetime.dt.hour
    data['pickup_minute_of_day'] = np.round((data.pickup_datetime.dt.hour * 60 + \
                                             data.pickup_datetime.dt.minute + \
                                             data.pickup_datetime.dt.second / 60)).astype(int)
    data['pickup_quarter_hour']  = np.round((data.pickup_datetime.dt.hour * 4 + \
                                            (data.pickup_datetime.dt.minute + 
                                             data.pickup_datetime.dt.second / 60) / 15)).astype(int)
    data['holiday']              = data.pickup_datetime.dt.date.astype('datetime64[ns]'). \
                                             isin(ny_public_holidays).astype(int)
    data['distance_great_circle']= great_circle_distance(data['pickup_latitude'].values, 
                                                          data['pickup_longitude'].values, 
                                                          data['dropoff_latitude'].values, 
                                                          data['dropoff_longitude'].values)
    data['distance_manhattan']   = manhattan_distance(data['pickup_latitude'].values, 
                                                      data['pickup_longitude'].values, 
                                                      data['dropoff_latitude'].values, 
                                                      data['dropoff_longitude'].values)
    data['direction']            = bearing(data['pickup_latitude'].values, data['pickup_longitude'].values, 
                                                 data['dropoff_latitude'].values, data['dropoff_longitude'].values)
    data['center_latitude']      = (data['pickup_latitude'].values  + data['dropoff_latitude'].values) / 2
    data['center_longitude']     = (data['pickup_longitude'].values + data['dropoff_longitude'].values) / 2
    temp_pickup                  = pca.transform(data[['pickup_latitude', 'pickup_longitude']])
    temp_center                  = pca.transform(data[['center_latitude', 'center_longitude']])
    temp_dropoff                 = pca.transform(data[['dropoff_latitude', 'dropoff_longitude']])
    data['pickup_pca0']          = temp_pickup[:, 0]
    data['pickup_pca1']          = temp_pickup[:, 1]
    data['center_pca0']          = temp_center[:, 0]
    data['center_pca1']          = temp_center[:, 1]
    data['dropoff_pca0']         = temp_dropoff[:, 0]
    data['dropoff_pca1']         = temp_dropoff[:, 1]
    data['pickup_cluster']       = kmeans.predict(data[['pickup_latitude',  'pickup_longitude']])
    data['center_cluster']       = kmeans.predict(data[['center_latitude',  'center_longitude']])
    data['dropoff_cluster']      = kmeans.predict(data[['dropoff_latitude', 'dropoff_longitude']])
    
# fields only on train dataframe (used for identifying problem rows, not for model training)
# train['speed_great_circle'] = train.distance_great_circle / train.trip_duration * 60 * 60
# train['speed_manhattan']    = train.distance_manhattan / train.trip_duration * 60 * 60
train['log_trip_duration']  = np.log(train['trip_duration'] + 1)
train_y = train.log_trip_duration

fr1 = pd.read_csv('./data/fastest_routes_train_part_1.csv', usecols=['id','total_distance','total_travel_time','number_of_steps'])
fr2 = pd.read_csv('./data/fastest_routes_train_part_2.csv', usecols=['id', 'total_distance','total_travel_time','number_of_steps'])
test_street_info = pd.read_csv('./data/fastest_routes_test.csv',usecols=['id','total_distance','total_travel_time','number_of_steps'])
train_street_info = pd.concat((fr1, fr2))
train = train.merge(train_street_info, how='left', on='id')
test  = test.merge(test_street_info,   how='left', on='id')

train_backup = train.copy()


CPU times: user 34.3 s, sys: 6.55 s, total: 40.9 s
Wall time: 22 s

In [45]:
#adding weather gives worse results!!!
# weather = pd.read_csv('./data/KNYC_Metars.csv', parse_dates=['Time'])
# weather.head(3)

# weather['snow']= 1*(weather.Events=='Snow') + 1*(weather.Events=='Fog\n\t,\nSnow')
# weather['year'] = weather['Time'].dt.year
# weather['pickup_month_of_year'] = weather['Time'].dt.month
# weather['pickup_day_of_month'] = weather['Time'].dt.day
# weather['pickup_hour_of_day'] = weather['Time'].dt.hour
# # weather = weather[weather['year'] == 2016][['pickup_month_of_year','pickup_day_of_month','pickup_hour_of_day',
# #                                             'Temp.','Windchill', 'Heat Index','Humidity','Pressure', 'Dew Point', 
# #                                             'Visibility','Wind Speed','Gust Speed', 'Precip','snow']]
# weather = weather[weather['year'] == 2016][['pickup_month_of_year','pickup_day_of_month','pickup_hour_of_day',
#                                             'Dew Point', 'Temp.', 'Pressure']]
# weather.head(3)

# train = pd.merge(train, weather, on=['pickup_month_of_year', 'pickup_day_of_month', 'pickup_hour_of_day'], how='left')
# test =  pd.merge(test,  weather, on=['pickup_month_of_year', 'pickup_day_of_month', 'pickup_hour_of_day'], how='left')
# train_backup = train.copy()


Out[45]:
Time Temp. Windchill Heat Index Humidity Pressure Dew Point Visibility Wind Dir Wind Speed Gust Speed Precip Events Conditions
0 2015-12-31 02:00:00 7.8 7.1 NaN 0.89 1017.0 6.1 8.0 NNE 5.6 0.0 0.8 None Overcast
1 2015-12-31 03:00:00 7.2 5.9 NaN 0.90 1016.5 5.6 12.9 Variable 7.4 0.0 0.3 None Overcast
2 2015-12-31 04:00:00 7.2 NaN NaN 0.90 1016.7 5.6 12.9 Calm 0.0 0.0 0.0 None Overcast
Out[45]:
pickup_month_of_year pickup_day_of_month pickup_hour_of_day Dew Point Temp. Pressure
22 1 1 0 -2.2 5.6 1018.8
23 1 1 1 -3.3 5.6 1018.5
24 1 1 2 -3.9 5.6 1017.9

In [72]:
# adding in dropoff and pickup cluster details - makes score worse!!
# group_freq = '60min'
# df_all = pd.concat((train, test))[['id', 'pickup_datetime', 'pickup_cluster', 'dropoff_cluster']]
# train['pickup_datetime_group'] = train['pickup_datetime'].dt.round(group_freq)
# test['pickup_datetime_group'] = test['pickup_datetime'].dt.round(group_freq)

# # Count trips over 60min
# df_counts = df_all.set_index('pickup_datetime')[['id']].sort_index()
# df_counts['count_60min'] = df_counts.isnull().rolling(group_freq).count()['id']
# train = train.merge(df_counts, on='id', how='left')
# test = test.merge(df_counts, on='id', how='left')

# # Count how many trips are going to each cluster over time
# dropoff_counts = df_all \
#     .set_index('pickup_datetime') \
#     .groupby([pd.TimeGrouper(group_freq), 'dropoff_cluster']) \
#     .agg({'id': 'count'}) \
#     .reset_index().set_index('pickup_datetime') \
#     .groupby('dropoff_cluster').rolling('240min').mean() \
#     .drop('dropoff_cluster', axis=1) \
#     .reset_index().set_index('pickup_datetime').shift(freq='-120min').reset_index() \
#     .rename(columns={'pickup_datetime': 'pickup_datetime_group', 'id': 'dropoff_cluster_count'})

# train['dropoff_cluster_count'] = train[['pickup_datetime_group', 'dropoff_cluster']]. \
#         merge(dropoff_counts, on=['pickup_datetime_group', 'dropoff_cluster'], how='left')['dropoff_cluster_count']. \
#         fillna(0)
# test['dropoff_cluster_count'] = test[['pickup_datetime_group', 'dropoff_cluster']]. \
#         merge(dropoff_counts, on=['pickup_datetime_group', 'dropoff_cluster'], how='left')['dropoff_cluster_count'].fillna(0)

# df_all = pd.concat((train, test))[['id', 'pickup_datetime', 'pickup_cluster', 'dropoff_cluster']]
# pickup_counts = df_all \
#     .set_index('pickup_datetime') \
#     .groupby([pd.TimeGrouper(group_freq), 'pickup_cluster']) \
#     .agg({'id': 'count'}) \
#     .reset_index().set_index('pickup_datetime') \
#     .groupby('pickup_cluster').rolling('240min').mean() \
#     .drop('pickup_cluster', axis=1) \
#     .reset_index().set_index('pickup_datetime').shift(freq='-120min').reset_index() \
#     .rename(columns={'pickup_datetime': 'pickup_datetime_group', 'id': 'pickup_cluster_count'})

# train['pickup_cluster_count'] = train[['pickup_datetime_group', 'pickup_cluster']].merge(pickup_counts, on=['pickup_datetime_group', 'pickup_cluster'], how='left')['pickup_cluster_count'].fillna(0)
# test['pickup_cluster_count'] = test[['pickup_datetime_group', 'pickup_cluster']].merge(pickup_counts, on=['pickup_datetime_group', 'pickup_cluster'], how='left')['pickup_cluster_count'].fillna(0)

# train = train.drop(['count_60min','pickup_datetime_group'], axis=1)
# test  = test.drop(['count_60min','pickup_datetime_group'], axis=1)

# train_backup = train.copy()

Perform EDA on fields


In [75]:
train.head(3)
test.head(3)

train.shape
test.shape


Out[75]:
id vendor_id pickup_datetime dropoff_datetime passenger_count pickup_longitude pickup_latitude dropoff_longitude dropoff_latitude store_and_fwd_flag trip_duration pickup_month_of_year pickup_day_of_week pickup_day_of_month pickup_day_of_year pickup_hour_of_day pickup_minute_of_day pickup_quarter_hour holiday distance_great_circle distance_manhattan direction center_latitude center_longitude pickup_pca0 pickup_pca1 center_pca0 center_pca1 dropoff_pca0 dropoff_pca1 pickup_cluster center_cluster dropoff_cluster speed_great_circle speed_manhattan log_trip_duration total_distance total_travel_time number_of_steps dropoff_cluster_count pickup_cluster_count
0 id2875421 2 2016-03-14 17:24:55 2016-03-14 17:32:30 1 -73.982155 40.767937 -73.964630 40.765602 0 455 3 0 14 74 17 1045 70 0 1.498521 1.735433 99.970196 40.766769 -73.973392 0.007691 0.017053 -0.000988 0.015374 -0.009667 0.013695 29 10 95 11.856428 13.730901 6.122493 2009.1 164.9 5.0 8.50 25.25
1 id2377394 1 2016-06-12 00:43:35 2016-06-12 00:54:38 1 -73.980415 40.738564 -73.999481 40.731152 0 663 6 6 12 164 0 44 3 0 1.805507 2.430506 -117.153768 40.734858 -73.989948 0.007677 -0.012371 0.017411 -0.015512 0.027145 -0.018652 27 93 96 9.803659 13.197318 6.498282 2513.2 332.0 6.0 6.25 6.00
2 id3858529 2 2016-01-19 11:35:24 2016-01-19 12:10:48 1 -73.979027 40.763939 -74.005333 40.710087 0 2124 1 1 19 19 11 695 46 0 6.385098 8.203575 -159.680165 40.737013 -73.992180 0.004803 0.012879 0.019513 -0.013229 0.034222 -0.039337 65 93 85 10.822201 13.904365 7.661527 11060.8 767.6 16.0 8.00 13.00
Out[75]:
id vendor_id pickup_datetime passenger_count pickup_longitude pickup_latitude dropoff_longitude dropoff_latitude store_and_fwd_flag pickup_month_of_year pickup_day_of_week pickup_day_of_month pickup_day_of_year pickup_hour_of_day pickup_minute_of_day pickup_quarter_hour holiday distance_great_circle distance_manhattan direction center_latitude center_longitude pickup_pca0 pickup_pca1 center_pca0 center_pca1 dropoff_pca0 dropoff_pca1 pickup_cluster center_cluster dropoff_cluster total_distance total_travel_time number_of_steps dropoff_cluster_count pickup_cluster_count
0 id3004672 1 2016-06-30 23:59:58 1 -73.988129 40.732029 -73.990173 40.756680 0 6 3 30 182 23 1440 96 0 2.746426 2.913304 -3.595224 40.744354 -73.989151 0.015761 -0.018442 0.016058 -0.006078 0.016356 0.006286 11 38 84 3795.9 424.6 4 0.0 0.0
1 id3505355 1 2016-06-30 23:59:53 1 -73.964203 40.679993 -73.959808 40.655403 0 6 3 30 182 23 1440 96 0 2.759239 3.104805 172.278835 40.667698 -73.962006 -0.005072 -0.071792 -0.006544 -0.084195 -0.008016 -0.096597 8 8 57 2904.5 200.0 4 0.0 0.0
2 id1217141 1 2016-06-30 23:59:47 1 -73.997437 40.737583 -73.986160 40.729523 0 6 3 30 182 23 1440 96 0 1.306155 1.846340 133.326248 40.733553 -73.991798 0.024727 -0.012352 0.019335 -0.016705 0.013943 -0.021059 42 93 11 1499.5 193.2 4 0.0 0.0
Out[75]:
(1458640, 41)
Out[75]:
(625134, 36)

In [236]:
# check distribution of vendor_id
_ = plt.figure(figsize=(18,6))
_ = plt.subplot(131)
_ = sns.countplot(train.vendor_id)

_ = plt.subplot(132)
_ = sns.barplot(x=train.vendor_id, y=train.trip_duration, ci=None)

_ = plt.subplot(133)
_ = plt.title('Trip Duration Distribution by Vendor Id')
_ = sns.distplot(train[(train.trip_duration<2500) & (train.vendor_id==2)].trip_duration, bins=100, kde=False)
_ = sns.distplot(train[(train.trip_duration<2500) & (train.vendor_id==1)].trip_duration, bins=100, kde=False)

# confidence intervals dont overlap so there IS a statistical difference
# import statsmodels.stats.api as sms
# dist2 = train[train.vendor_id==2].trip_duration.values
# dist1 = train[train.vendor_id==1].trip_duration.values
# dist1.mean(), sms.DescrStatsW(dist1).tconfint_mean()
# dist2.mean(), sms.DescrStatsW(dist2).tconfint_mean()



In [237]:
#check number of trips by various time periods
print('Datetime Range', train.pickup_datetime.min(), '->', train.pickup_datetime.max())

_ = plt.figure(figsize=(18,6))
_ = plt.title("Trips per day")
_ = sns.countplot(train.pickup_day_of_year)
_ = plt.xlim(-1,365//2)

for holiday in ny_public_holidays.dt.dayofyear:
    _ = plt.axvline(x=holiday-1, color='r', linestyle='--')
    
_ = plt.figure(figsize=(18,6))
_ = plt.title("Trips per Quarter Hour during day")
_ = sns.countplot(train.pickup_quarter_hour)

_ = plt.figure(figsize=(18,6))
_ = plt.subplot(141)
_ = plt.title("Trips per day of week")
_ = sns.countplot(train.pickup_day_of_week)

_ = plt.subplot(142)
_ = plt.title("Trips per day of month")
_ = sns.countplot(train.pickup_day_of_month)

_ = plt.subplot(143)
_ = plt.title("Trips per hour of day")
_ = sns.countplot(train.pickup_hour_of_day)

_ = plt.subplot(144)
_ = plt.title("Trips per Month")
_ = sns.countplot(train.pickup_month_of_year)

_ = plt.tight_layout()


Datetime Range 2016-01-01 00:00:17 -> 2016-06-30 23:59:39

In [238]:
# show trip durations by various time periods
_ = plt.figure(figsize=(18,6))
_ = plt.title("Trip Duration by day of year")
_ = sns.barplot(x=train.pickup_day_of_year, y=train.trip_duration, ci=None)
for holiday in ny_public_holidays.dt.dayofyear:
    _ = plt.axvline(x=holiday-1, color='r', linestyle='--')
    
_ = plt.figure(figsize=(18,6))
_ = plt.title("Trip Duration by Quarter Hour during day")
_ = sns.barplot(x=train.pickup_quarter_hour, y=train.trip_duration, ci=None)

_ = plt.figure(figsize=(18,6))
_ = plt.subplot(141)
_ = plt.title("Trip Duration per day of week")
_ = sns.barplot(x=train.pickup_day_of_week, y=train.trip_duration, ci=None)

_ = plt.subplot(142)
_ = plt.title("Trip Duration per day of month")
_ = sns.barplot(x=train.pickup_day_of_month, y=train.trip_duration, ci=None)

_ = plt.subplot(143)
_ = plt.title("Trip Duration per hour of day")
_ = sns.barplot(x=train.pickup_hour_of_day, y=train.trip_duration, ci=None)

_ = plt.subplot(144)
_ = plt.title("Trip Duration per Month")
_ = sns.barplot(x=train.pickup_month_of_year, y=train.trip_duration, ci=None)

# check distribution of holiday flag
_ = plt.figure(figsize=(18,6))
_ = plt.subplot(141)
_ = sns.countplot(train.holiday)

_ = plt.subplot(142)
_ = plt.title("Trip Duration by Holiday Flag")
_ = sns.barplot(x=train.holiday, y=train.trip_duration, ci=None)

_ = plt.subplot(143)
_ = plt.title('Trip Duration on Holidays')
_ = sns.distplot(train[(train.trip_duration<2500) & (train.holiday)].trip_duration, bins=50, kde=False)
_ = plt.subplot(144)
_ = plt.title('Trip Duration on NON-Holidays')
_ = sns.distplot(train[(train.trip_duration<2500) & ~(train.holiday)].trip_duration, bins=50, kde=False)

_ = plt.tight_layout()



In [239]:
# check distribution of passenger_count
#train.passenger_count.value_counts()

_ = plt.figure(figsize=(18,6))
_ = plt.subplot(121)
_ = sns.countplot(train.passenger_count)

_ = plt.subplot(122)
_ = plt.title("Trip Duration by Passenger Count")
_ = sns.barplot(x=train.passenger_count, y=train.trip_duration, ci=None)
_ = plt.show()

# confidence intervals dont overlap so there IS a statistical difference
import statsmodels.stats.api as sms
print('Mean trip duration and confidence intervals for trip duration for each passenger count')
for count in sorted(train.passenger_count.unique()):
    distribution = train[train.passenger_count==count].trip_duration.values
    count, distribution.mean(), sms.DescrStatsW(distribution).tconfint_mean()


Mean trip duration and confidence intervals for trip duration for each passenger count
Out[239]:
(0, 1718.4333333333334, (-1141.8081375960392, 4578.6748042627059))
Out[239]:
(1, 922.9584727010257, (917.31867619429613, 928.59826920775527))
Out[239]:
(2, 995.71793055245178, (982.02972072384523, 1009.4061403810583))
Out[239]:
(3, 1028.2362762121011, (998.45478378980408, 1058.017768634398))
Out[239]:
(4, 1053.5297493310802, (1009.4563394841388, 1097.6031591780215))
Out[239]:
(5, 1070.2321739575864, (1039.5145211999172, 1100.9498267152555))
Out[239]:
(6, 1061.3552231394699, (1022.3929175627042, 1100.3175287162355))
Out[239]:
(7, 19.666666666666668, (7.1634477074449006, 32.169885625888433))
/Users/graham/anaconda/lib/python3.6/site-packages/statsmodels/stats/weightstats.py:224: RuntimeWarning: invalid value encountered in double_scalars
  return std / np.sqrt(self.sum_weights - 1)
Out[239]:
(8, 104.0, (nan, nan))
Out[239]:
(9, 560.0, (nan, nan))

In [240]:
# check distribution of store and forward flag
#train.store_and_fwd_flag.value_counts()

_ = plt.figure(figsize=(18,6))
_ = plt.subplot(141)
_ = sns.countplot(train.store_and_fwd_flag)

_ = plt.subplot(142)
_ = plt.title("Trip Duration by Store and Forward Flag")
_ = sns.barplot(x=train.store_and_fwd_flag, y=train.trip_duration, ci=None)

_ = plt.subplot(143)
_ = plt.title("Trip Duration with Store and Forward Flag=False")
_ = sns.distplot(train[(train.trip_duration<2500) & (train.store_and_fwd_flag==0)].trip_duration, bins=50, kde=False)
_ = plt.subplot(144)
_ = plt.title("Trip Duration with Store and Forward Flag=True")
_ = sns.distplot(train[(train.trip_duration<2500) & (train.store_and_fwd_flag==1)].trip_duration, bins=50, kde=False)



In [241]:
# check distribution of distance (great circle) - maybe should model on log(dist) to get a more normal distribution

_ = plt.figure(figsize=(18,6))
_ = plt.subplot(121)
_ = plt.title("Trip Distance Distribution (great circle)")
_ = sns.distplot(train.distance_great_circle, bins=100, kde=False)

_ = plt.subplot(122)
_ = plt.title("Trip Distance Distribution (great circle) < 50km")
_ = sns.distplot(train[train.distance_great_circle<25].distance_great_circle,bins=100, kde=False)



In [242]:
# check clustering is working ok
N= 200000 # filter a subset for faster plotting
_ = plt.figure(figsize=(18,12))
_ = plt.scatter(train.pickup_longitude.values[:N], train.pickup_latitude.values[:N], s=10, lw=0,
           c=train.pickup_cluster[:N].values, cmap='tab20', alpha=0.2)
_ = plt.xlim((-74.05, -73.75))
_ = plt.ylim((40.63, 40.88))
_ = plt.xlabel('Longitude')
_ = plt.ylabel('Latitude')



In [243]:
# investigate overall trip duration distribution
_ = plt.figure(figsize=(18,6))
_ = plt.title('Long Duration Trips')
_ = sns.distplot(train.trip_duration[train.trip_duration> 22*60*60], bins=200, kde=False)

_ = plt.figure(figsize=(18,6))
_ = plt.title('Middle Duration Trips')
_ = sns.distplot(train.trip_duration[train.trip_duration< 60*60], bins=200, kde=False)

_ = plt.figure(figsize=(18,6))
_ = plt.title('Short Duration Trips')
_ = sns.distplot(train.trip_duration[train.trip_duration< 5*60], bins=299, kde=False)



In [12]:
%%time
# scatter plot of all fields vs trip_duration - takes a LONG time to run

_ = plt.figure(figsize=(18,40))
fields = [field for field in train.columns 
          if train[field].dtype in [np.int64, np.float64] and field not in ['trip_duration','log_trip_duration']]

for count, field in enumerate(fields):
        _ = plt.subplot(len(fields) // 3 + 1, 3, count+1)
        _ = plt.scatter(x=field, y='trip_duration', data=train, s=5, alpha=0.3, marker='o')
        _ = plt.title(field + ' vs Trip Duration')
        _ = plt.xlabel(field)
        _ = plt.ylabel('trip_duration')
plt.tight_layout()


CPU times: user 49.2 s, sys: 397 ms, total: 49.6 s
Wall time: 49.8 s

In [99]:
# check for (linear) correlations between predictor variables and trip_duration
corr = np.round(train.corr(),2)
_ = plt.figure(figsize=(18,14))
_ = sns.heatmap(corr, xticklabels=corr.columns.values, yticklabels=corr.columns.values, annot=True)


Prepare Data for modelling


In [136]:
# create data for model training/validation and filter to optimise training
from sklearn.model_selection import train_test_split
from sklearn.preprocessing import StandardScaler

train = train_backup.copy() # refresh train from backup (to allow repeated filtering below)
train_y = train.log_trip_duration

drop_rows  = np.concatenate([
    train[train.trip_duration > 4000].index.values, # remove long duration trips to improve XGBoost
    ]) 

drop_columns = ['id', 'pickup_datetime', 'dropoff_datetime', 'trip_duration', 
                'log_trip_duration', 'speed_great_circle', 'speed_manhattan']
feature_names = [feature for feature in train.columns if feature not in drop_columns]

Xtrain, Xvalid, ytrain, yvalid = train_test_split(train[feature_names], train_y, test_size=0.1, random_state=2)
Xtest = test[feature_names]

# filter training set only (should NOT filter validation set)
print('Before Xtrain= {0}, Xvalid= {1}, Xtest= {2}'.format(Xtrain.shape, Xvalid.shape, Xtest.shape))

# filtering not required for XGBoost
# Xtrain = Xtrain[(Xtrain.trip_duration < 24 * 60 * 60) &  # get rid of 'noisy' long trips that skew predictions
#              (~Xtrain.passenger_count.isin([0,7,8,9])) &
#              (Xtrain.pickup_latitude > 40)    & (Xtrain.pickup_latitude < 41.5) &
#               (Xtrain.pickup_longitude > -75) & (Xtrain.pickup_longitude < -73) &
#              (Xtrain.distance_great_circle < 99) &
#              ~((Xtrain.speed_great_circle > 60) & (Xtrain.trip_duration < 60)) &
#              (Xtrain.speed_great_circle < 120)].index

Xtrain = Xtrain.drop(drop_rows, errors='ignore')
ytrain = ytrain.drop(drop_rows, errors='ignore')
print('After  Xtrain= {0}, Xvalid= {1}, Xtest= {2}'.format(Xtrain.shape, Xvalid.shape, Xtest.shape))

# scaling doesnt seem to do much for Ridge, but it does make coefs represent importance
# scaler = StandardScaler()
# _ = scaler.fit(train[feature_names])
# Xtrain_sc = scaler.transform(Xtrain)
# Xvalid_sc = scaler.transform(Xvalid)
# Xtest_sc  = scaler.transform(Xtest)


Before Xtrain= (1312776, 32), Xvalid= (145864, 32), Xtest= (625134, 32)
After  Xtrain= (1305276, 32), Xvalid= (145864, 32), Xtest= (625134, 32)

XGBoost Model and Submission Generation

Performs really well (as usual)


In [151]:
%%time
import xgboost as xgb
from sklearn.metrics import mean_squared_error

dtrain = xgb.DMatrix(Xtrain, label=ytrain)
dvalid = xgb.DMatrix(Xvalid, label=yvalid)
watchlist = [(dtrain, 'train'), (dvalid, 'valid')]

# manually optimised, initially from kaggle
params_m = {'min_child_weight': 28, 'eta': 0.17, 'colsample_bytree': 0.54, 'max_depth': 16,
          'subsample': 0.95, 'lambda': 1, 'nthread': 8, 'booster' : 'gbtree', 'silent': 1,
          'eval_metric': 'rmse', 'objective': 'reg:linear'}

# from scikit-optimize [133, 0.17936020611338641, 0.70459161599199072, 64, 1.0, 24.2701922969149, 0]
params_s = {'min_child_weight': 133, 'eta': 0.17936, 'colsample_bytree': 0.70459, 'max_depth': 64,
          'subsample': 1.0, 'lambda': 24.27, 'gamma': 0, 'nthread': 8, 'booster' : 'gbtree', 'silent': 1,
          'eval_metric': 'rmse', 'objective': 'reg:linear'}

XGmodel = xgb.train(params=params_s, dtrain=dtrain, num_boost_round=800, evals=watchlist, early_stopping_rounds=50, 
                    maximize=False, verbose_eval=10)

XGtrain_preds = XGmodel.predict(dtrain)
XGvalid_preds = XGmodel.predict(dvalid)
print('\nTrain  RMSE =', round(np.sqrt(mean_squared_error(ytrain, XGtrain_preds)),6))
print('Validn RMSE =', round(np.sqrt(mean_squared_error(yvalid, XGvalid_preds)),6))


[0]	train-rmse:4.93095	valid-rmse:4.94847
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.777307	valid-rmse:0.808111
[20]	train-rmse:0.338761	valid-rmse:0.395887
[30]	train-rmse:0.297289	valid-rmse:0.37005
[40]	train-rmse:0.278907	valid-rmse:0.36514
[50]	train-rmse:0.265811	valid-rmse:0.363451
[60]	train-rmse:0.259875	valid-rmse:0.363167
[70]	train-rmse:0.256904	valid-rmse:0.363079
[80]	train-rmse:0.254767	valid-rmse:0.363147
[90]	train-rmse:0.25158	valid-rmse:0.363215
[100]	train-rmse:0.247844	valid-rmse:0.36303
[110]	train-rmse:0.245152	valid-rmse:0.363089
[120]	train-rmse:0.243569	valid-rmse:0.363155
[130]	train-rmse:0.240284	valid-rmse:0.362881
[140]	train-rmse:0.238333	valid-rmse:0.36295
[150]	train-rmse:0.237087	valid-rmse:0.36314
[160]	train-rmse:0.235969	valid-rmse:0.363181
[170]	train-rmse:0.23457	valid-rmse:0.363267
[180]	train-rmse:0.232045	valid-rmse:0.363283
Stopping. Best iteration:
[132]	train-rmse:0.239957	valid-rmse:0.362816


Train  RMSE = 0.231848
Validn RMSE = 0.363328
CPU times: user 2h 19min 21s, sys: 23.5 s, total: 2h 19min 44s
Wall time: 21min 21s

In [152]:
feature_importance = pd.Series(index = Xtrain.columns, data = XGmodel.get_fscore())
_ = feature_importance.sort_values(ascending=True).head(40).plot(kind='barh', color="r", figsize = (18,12))



In [153]:
dtest = xgb.DMatrix(Xtest)
XGlog_test_preds = XGmodel.predict(dtest)
XGtest_preds = np.exp(XGlog_test_preds) - 1
XGpreds = pd.DataFrame({'id': test_id, 'trip_duration': XGtest_preds})
XGpreds.to_csv('XG_submission.csv.gz', index=False, compression='gzip')

XGBoost model hyperparameter search - scikit optimise


In [141]:
# create a cut down training set to reduce training time
sample_size = 200000
print('Total training size',len(Xtrain))
print('Train sample size =', sample_size)
train_samples = np.random.choice(Xtrain.index, size=sample_size)
Xtrain_small = Xtrain.loc[train_samples]
ytrain_small = ytrain.loc[train_samples]


Total training size 1305276
Train sample size = 200000

In [146]:
from skopt import gp_minimize
from sklearn.metrics import mean_squared_error
import xgboost as xgb

def objective(values): 
    params = {'min_child_weight': values[0], 
              'eta': values[1], 
              'colsample_bytree': values[2], 
              'max_depth': values[3],
              'subsample': values[4], 
              'lambda': values[5], 
              'gamma': values[6],
              'nthread': 8, 'booster' : 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
    print('\nNext set of params.....',params)
    XGmodel = xgb.train(params=params, dtrain=dtrain_opt, num_boost_round=40, evals=watchlist, early_stopping_rounds=50, 
                    maximize=False, verbose_eval=10)

    XGvalid_preds = XGmodel.predict(dvalid)
    return np.sqrt(mean_squared_error(yvalid, XGvalid_preds))

In [147]:
%%time
# Bayesian optimisation using Gaussian processes- calls objective function n_calls times
space = [(10, 300),    # min_child_weight
         (0.1, 0.3),   # eta
         (0.4, 1),     # colsample_bytree
         (5, 300),     # max_depth
         (0.8, 1),     # subsample
         (0.1, 90),    # lambda
         (0, 2),       # gamma
        ]

dtrain_opt = xgb.DMatrix(Xtrain_small, label=ytrain_small) # use cutdown training set
result = gp_minimize(objective, space, n_calls=800, random_state=0, verbose=True)


Iteration No: 1 started. Evaluating function at random point.

Next set of params..... {'min_child_weight': 169, 'eta': 0.24303787327448392, 'colsample_bytree': 0.76165802564298635, 'max_depth': 111, 'subsample': 0.88473095986778094, 'lambda': 58.165880764692403, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55617	valid-rmse:4.57455
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.479773	valid-rmse:0.51989
[20]	train-rmse:0.348796	valid-rmse:0.394411
[30]	train-rmse:0.338764	valid-rmse:0.385468
[39]	train-rmse:0.334927	valid-rmse:0.382512
Iteration No: 1 ended. Evaluation done at random point.
Time taken: 11.1970
Function value obtained: 0.3825
Current minimum: 0.3825
Iteration No: 2 started. Evaluating function at random point.

Next set of params..... {'min_child_weight': 269, 'eta': 0.29273255210020588, 'colsample_bytree': 0.63006491129546671, 'max_depth': 159, 'subsample': 0.90577898395058098, 'lambda': 51.167206042344532, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.26079	valid-rmse:4.27933
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.400194	valid-rmse:0.443665
[20]	train-rmse:0.349518	valid-rmse:0.394501
[30]	train-rmse:0.342579	valid-rmse:0.388407
[39]	train-rmse:0.339853	valid-rmse:0.386219
Iteration No: 2 ended. Evaluation done at random point.
Time taken: 9.6680
Function value obtained: 0.3862
Current minimum: 0.3825
Iteration No: 3 started. Evaluating function at random point.

Next set of params..... {'min_child_weight': 31, 'eta': 0.11742585994030814, 'colsample_bytree': 0.41213103846419546, 'max_depth': 167, 'subsample': 0.95563135018997014, 'lambda': 78.31409212738906, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.30247	valid-rmse:5.32061
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.58718	valid-rmse:1.61017
[20]	train-rmse:0.596603	valid-rmse:0.63298
[30]	train-rmse:0.390949	valid-rmse:0.436297
[39]	train-rmse:0.357104	valid-rmse:0.403759
Iteration No: 3 ended. Evaluation done at random point.
Time taken: 5.3762
Function value obtained: 0.4038
Current minimum: 0.3825
Iteration No: 4 started. Evaluating function at random point.

Next set of params..... {'min_child_weight': 242, 'eta': 0.19229587245058638, 'colsample_bytree': 0.86831750577187339, 'max_depth': 28, 'subsample': 0.92798420426550476, 'lambda': 12.987460538073275, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85519	valid-rmse:4.8732
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.692715	valid-rmse:0.72533
[20]	train-rmse:0.359073	valid-rmse:0.405093
[30]	train-rmse:0.342846	valid-rmse:0.389398
[39]	train-rmse:0.339174	valid-rmse:0.386057
Iteration No: 4 ended. Evaluation done at random point.
Time taken: 11.4492
Function value obtained: 0.3861
Current minimum: 0.3825
Iteration No: 5 started. Evaluating function at random point.

Next set of params..... {'min_child_weight': 161, 'eta': 0.18293238799810474, 'colsample_bytree': 0.55873336726277623, 'max_depth': 156, 'subsample': 0.89123006644330971, 'lambda': 51.202212003291514, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9127	valid-rmse:4.93101
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.77104	valid-rmse:0.802081
[20]	train-rmse:0.370792	valid-rmse:0.416144
[30]	train-rmse:0.341847	valid-rmse:0.388952
[39]	train-rmse:0.334905	valid-rmse:0.383101
Iteration No: 5 ended. Evaluation done at random point.
Time taken: 7.6782
Function value obtained: 0.3831
Current minimum: 0.3825
Iteration No: 6 started. Evaluating function at random point.

Next set of params..... {'min_child_weight': 189, 'eta': 0.2224191445444843, 'colsample_bytree': 0.77016039812485415, 'max_depth': 189, 'subsample': 0.9363640598206967, 'lambda': 32.41976026158337, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.6772	valid-rmse:4.69527
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.541295	valid-rmse:0.578947
[20]	train-rmse:0.34939	valid-rmse:0.396156
[30]	train-rmse:0.338428	valid-rmse:0.386092
[39]	train-rmse:0.334554	valid-rmse:0.382972
Iteration No: 6 ended. Evaluation done at random point.
Time taken: 11.0722
Function value obtained: 0.3830
Current minimum: 0.3825
Iteration No: 7 started. Evaluating function at random point.

Next set of params..... {'min_child_weight': 212, 'eta': 0.11204509432585397, 'colsample_bytree': 0.80006002926740072, 'max_depth': 136, 'subsample': 0.8420765122147682, 'lambda': 11.690474159171314, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.33288	valid-rmse:5.35085
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.67492	valid-rmse:1.69622
[20]	train-rmse:0.625849	valid-rmse:0.660202
[30]	train-rmse:0.389057	valid-rmse:0.433833
[39]	train-rmse:0.350875	valid-rmse:0.397428
Iteration No: 7 ended. Evaluation done at random point.
Time taken: 8.0236
Function value obtained: 0.3974
Current minimum: 0.3825
Iteration No: 8 started. Evaluating function at random point.

Next set of params..... {'min_child_weight': 115, 'eta': 0.21403935408357594, 'colsample_bytree': 0.66316090807739236, 'max_depth': 198, 'subsample': 0.82040896214960568, 'lambda': 18.878020372925647, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.72629	valid-rmse:4.7443
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.573582	valid-rmse:0.609933
[20]	train-rmse:0.347113	valid-rmse:0.394668
[30]	train-rmse:0.334109	valid-rmse:0.383965
[39]	train-rmse:0.32971	valid-rmse:0.381353
Iteration No: 8 ended. Evaluation done at random point.
Time taken: 11.9743
Function value obtained: 0.3814
Current minimum: 0.3814
Iteration No: 9 started. Evaluating function at random point.

Next set of params..... {'min_child_weight': 199, 'eta': 0.15065832050795644, 'colsample_bytree': 0.67978646371378382, 'max_depth': 53, 'subsample': 0.83179391672910397, 'lambda': 10.022725190671034, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.10283	valid-rmse:5.12075
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.0737	valid-rmse:1.09939
[20]	train-rmse:0.411689	valid-rmse:0.45513
[30]	train-rmse:0.347344	valid-rmse:0.393912
[39]	train-rmse:0.339156	valid-rmse:0.38629
Iteration No: 9 ended. Evaluation done at random point.
Time taken: 8.8471
Function value obtained: 0.3863
Current minimum: 0.3814
Iteration No: 10 started. Evaluating function at random point.

Next set of params..... {'min_child_weight': 50, 'eta': 0.13931647233601072, 'colsample_bytree': 0.62123510239657853, 'max_depth': 165, 'subsample': 0.81942025515861228, 'lambda': 75.431247184142492, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.17256	valid-rmse:5.19074
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.23374	valid-rmse:1.25914
[20]	train-rmse:0.463937	valid-rmse:0.506017
[30]	train-rmse:0.358759	valid-rmse:0.406712
[39]	train-rmse:0.341001	valid-rmse:0.390742
Iteration No: 10 ended. Evaluation done at random point.
Time taken: 7.7456
Function value obtained: 0.3907
Current minimum: 0.3814
Iteration No: 11 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 5, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21192	valid-rmse:4.22956
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.404346	valid-rmse:0.446388
[20]	train-rmse:0.368841	valid-rmse:0.411431
[30]	train-rmse:0.360016	valid-rmse:0.40309
[39]	train-rmse:0.35581	valid-rmse:0.399475
Iteration No: 11 ended. Search finished for the next optimal point.
Time taken: 3.9856
Function value obtained: 0.3995
Current minimum: 0.3814
Iteration No: 12 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.23721093674286556, 'colsample_bytree': 0.40000000000000002, 'max_depth': 5, 'subsample': 0.80000000000000004, 'lambda': 90.0, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.59213	valid-rmse:4.61051
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.515291	valid-rmse:0.554142
[20]	train-rmse:0.383146	valid-rmse:0.425983
[30]	train-rmse:0.369024	valid-rmse:0.412429
[39]	train-rmse:0.363543	valid-rmse:0.407431
Iteration No: 12 ended. Search finished for the next optimal point.
Time taken: 2.7372
Function value obtained: 0.4074
Current minimum: 0.3814
Iteration No: 13 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.29999999999999999, 'colsample_bytree': 0.40000000000000002, 'max_depth': 5, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21247	valid-rmse:4.22993
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.406212	valid-rmse:0.448665
[20]	train-rmse:0.368158	valid-rmse:0.411716
[30]	train-rmse:0.358239	valid-rmse:0.402627
[39]	train-rmse:0.354405	valid-rmse:0.399382
Iteration No: 13 ended. Search finished for the next optimal point.
Time taken: 2.6971
Function value obtained: 0.3994
Current minimum: 0.3814
Iteration No: 14 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.23133212970566921, 'colsample_bytree': 1.0, 'max_depth': 5, 'subsample': 0.80000000000000004, 'lambda': 37.479895837702138, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.62438	valid-rmse:4.64264
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.520047	valid-rmse:0.55872
[20]	train-rmse:0.373373	valid-rmse:0.417238
[30]	train-rmse:0.362264	valid-rmse:0.406493
[39]	train-rmse:0.357876	valid-rmse:0.402456
Iteration No: 14 ended. Search finished for the next optimal point.
Time taken: 4.0327
Function value obtained: 0.4025
Current minimum: 0.3814
Iteration No: 15 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21026	valid-rmse:4.22769
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.373293	valid-rmse:0.419267
[20]	train-rmse:0.34279	valid-rmse:0.390797
[30]	train-rmse:0.338555	valid-rmse:0.387663
[39]	train-rmse:0.336548	valid-rmse:0.386314
Iteration No: 15 ended. Search finished for the next optimal point.
Time taken: 20.0753
Function value obtained: 0.3863
Current minimum: 0.3814
Iteration No: 16 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21001	valid-rmse:4.22741
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.371219	valid-rmse:0.416678
[20]	train-rmse:0.341954	valid-rmse:0.388446
[30]	train-rmse:0.338909	valid-rmse:0.386091
[39]	train-rmse:0.337319	valid-rmse:0.385005
Iteration No: 16 ended. Search finished for the next optimal point.
Time taken: 19.0071
Function value obtained: 0.3850
Current minimum: 0.3814
Iteration No: 17 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.22499701007990208, 'colsample_bytree': 0.40000000000000002, 'max_depth': 121, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.65791	valid-rmse:4.67531
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.515946	valid-rmse:0.554045
[20]	train-rmse:0.348652	valid-rmse:0.395366
[30]	train-rmse:0.338966	valid-rmse:0.387034
[39]	train-rmse:0.335082	valid-rmse:0.384551
Iteration No: 17 ended. Search finished for the next optimal point.
Time taken: 8.6739
Function value obtained: 0.3846
Current minimum: 0.3814
Iteration No: 18 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.10000000000000001, 'colsample_bytree': 1.0, 'max_depth': 5, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.40381	valid-rmse:5.42164
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.92421	valid-rmse:1.94432
[20]	train-rmse:0.766814	valid-rmse:0.797398
[30]	train-rmse:0.447721	valid-rmse:0.489138
[39]	train-rmse:0.386	valid-rmse:0.429772
Iteration No: 18 ended. Search finished for the next optimal point.
Time taken: 4.1829
Function value obtained: 0.4298
Current minimum: 0.3814
Iteration No: 19 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.23154623784238476, 'colsample_bytree': 0.66670960618433694, 'max_depth': 200, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.6191	valid-rmse:4.63648
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.488718	valid-rmse:0.527462
[20]	train-rmse:0.346882	valid-rmse:0.392448
[30]	train-rmse:0.341343	valid-rmse:0.386948
[39]	train-rmse:0.339132	valid-rmse:0.385262
Iteration No: 19 ended. Search finished for the next optimal point.
Time taken: 10.8692
Function value obtained: 0.3853
Current minimum: 0.3814
Iteration No: 20 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.18325361434009563, 'colsample_bytree': 1.0, 'max_depth': 110, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90625	valid-rmse:4.92378
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.737612	valid-rmse:0.771185
[20]	train-rmse:0.353413	valid-rmse:0.406764
[30]	train-rmse:0.338472	valid-rmse:0.392655
[39]	train-rmse:0.336196	valid-rmse:0.390659
Iteration No: 20 ended. Search finished for the next optimal point.
Time taken: 29.6053
Function value obtained: 0.3907
Current minimum: 0.3814
Iteration No: 21 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 62, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.20997	valid-rmse:4.22739
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.364641	valid-rmse:0.426523
[20]	train-rmse:0.34316	valid-rmse:0.409065
[30]	train-rmse:0.343407	valid-rmse:0.409713
[39]	train-rmse:0.343428	valid-rmse:0.410071
Iteration No: 21 ended. Search finished for the next optimal point.
Time taken: 37.9904
Function value obtained: 0.4101
Current minimum: 0.3814
Iteration No: 22 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.24753339754702527, 'colsample_bytree': 0.40000000000000002, 'max_depth': 200, 'subsample': 0.90906273721226816, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.52461	valid-rmse:4.54249
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.436959	valid-rmse:0.49261
[20]	train-rmse:0.338919	valid-rmse:0.40647
[30]	train-rmse:0.336974	valid-rmse:0.40552
[39]	train-rmse:0.336732	valid-rmse:0.405663
Iteration No: 22 ended. Search finished for the next optimal point.
Time taken: 26.7029
Function value obtained: 0.4057
Current minimum: 0.3814
Iteration No: 23 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.10000000000000001, 'colsample_bytree': 0.40000000000000002, 'max_depth': 200, 'subsample': 0.80000000000000004, 'lambda': 90.0, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.40637	valid-rmse:5.4245
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.9426	valid-rmse:1.96405
[20]	train-rmse:0.786213	valid-rmse:0.817354
[30]	train-rmse:0.457438	valid-rmse:0.498734
[39]	train-rmse:0.384942	valid-rmse:0.429203
Iteration No: 23 ended. Search finished for the next optimal point.
Time taken: 3.8833
Function value obtained: 0.4292
Current minimum: 0.3814
Iteration No: 24 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 158, 'eta': 0.20409393433866146, 'colsample_bytree': 0.40000000000000002, 'max_depth': 107, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.78247	valid-rmse:4.79998
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.609571	valid-rmse:0.644382
[20]	train-rmse:0.352485	valid-rmse:0.399348
[30]	train-rmse:0.341536	valid-rmse:0.388673
[39]	train-rmse:0.338269	valid-rmse:0.386016
Iteration No: 24 ended. Search finished for the next optimal point.
Time taken: 8.7659
Function value obtained: 0.3860
Current minimum: 0.3814
Iteration No: 25 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.16895176986632049, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99171	valid-rmse:5.0093
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.860191	valid-rmse:0.888521
[20]	train-rmse:0.36272	valid-rmse:0.411302
[30]	train-rmse:0.334521	valid-rmse:0.385635
[39]	train-rmse:0.330648	valid-rmse:0.382925
Iteration No: 25 ended. Search finished for the next optimal point.
Time taken: 20.1940
Function value obtained: 0.3829
Current minimum: 0.3814
Iteration No: 26 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 188, 'eta': 0.21259336366248757, 'colsample_bytree': 0.40000000000000002, 'max_depth': 123, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.73266	valid-rmse:4.75049
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.565852	valid-rmse:0.602319
[20]	train-rmse:0.347876	valid-rmse:0.395265
[30]	train-rmse:0.337482	valid-rmse:0.386153
[39]	train-rmse:0.334002	valid-rmse:0.384063
Iteration No: 26 ended. Search finished for the next optimal point.
Time taken: 9.3197
Function value obtained: 0.3841
Current minimum: 0.3814
Iteration No: 27 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 174, 'eta': 0.29999999999999999, 'colsample_bytree': 0.40000000000000002, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21907	valid-rmse:4.23748
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.401812	valid-rmse:0.445782
[20]	train-rmse:0.347978	valid-rmse:0.394724
[30]	train-rmse:0.336633	valid-rmse:0.385703
[39]	train-rmse:0.332053	valid-rmse:0.382878
Iteration No: 27 ended. Search finished for the next optimal point.
Time taken: 7.6011
Function value obtained: 0.3829
Current minimum: 0.3814
Iteration No: 28 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 84, 'eta': 0.20474918011832055, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.78378	valid-rmse:4.80194
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.631539	valid-rmse:0.666909
[20]	train-rmse:0.359221	valid-rmse:0.40602
[30]	train-rmse:0.343916	valid-rmse:0.391263
[39]	train-rmse:0.338953	valid-rmse:0.386973
Iteration No: 28 ended. Search finished for the next optimal point.
Time taken: 13.9339
Function value obtained: 0.3870
Current minimum: 0.3814
Iteration No: 29 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 208, 'eta': 0.27784115909013568, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.34214	valid-rmse:4.35954
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.385637	valid-rmse:0.431289
[20]	train-rmse:0.336602	valid-rmse:0.385869
[30]	train-rmse:0.332879	valid-rmse:0.384038
[39]	train-rmse:0.330858	valid-rmse:0.383379
Iteration No: 29 ended. Search finished for the next optimal point.
Time taken: 31.3260
Function value obtained: 0.3834
Current minimum: 0.3814
Iteration No: 30 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.29999999999999999, 'colsample_bytree': 0.45816822266155877, 'max_depth': 5, 'subsample': 0.81555513179531214, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21996	valid-rmse:4.23851
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.417219	valid-rmse:0.459257
[20]	train-rmse:0.375422	valid-rmse:0.417948
[30]	train-rmse:0.364118	valid-rmse:0.407103
[39]	train-rmse:0.358552	valid-rmse:0.401991
Iteration No: 30 ended. Search finished for the next optimal point.
Time taken: 2.7177
Function value obtained: 0.4020
Current minimum: 0.3814
Iteration No: 31 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 248, 'eta': 0.24310915105599318, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55617	valid-rmse:4.57441
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.484145	valid-rmse:0.524432
[20]	train-rmse:0.349382	valid-rmse:0.395862
[30]	train-rmse:0.337649	valid-rmse:0.385559
[39]	train-rmse:0.333203	valid-rmse:0.382191
Iteration No: 31 ended. Search finished for the next optimal point.
Time taken: 14.9248
Function value obtained: 0.3822
Current minimum: 0.3814
Iteration No: 32 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 287, 'eta': 0.11660164640936438, 'colsample_bytree': 0.83686856600285386, 'max_depth': 7, 'subsample': 0.99080423485662239, 'lambda': 60.180346764679733, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.30706	valid-rmse:5.3252
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.59646	valid-rmse:1.61909
[20]	train-rmse:0.599191	valid-rmse:0.634778
[30]	train-rmse:0.398074	valid-rmse:0.441725
[39]	train-rmse:0.368216	valid-rmse:0.412649
Iteration No: 32 ended. Search finished for the next optimal point.
Time taken: 4.7587
Function value obtained: 0.4126
Current minimum: 0.3814
Iteration No: 33 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 155, 'eta': 0.18279742852746411, 'colsample_bytree': 1.0, 'max_depth': 136, 'subsample': 0.80000000000000004, 'lambda': 90.0, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91459	valid-rmse:4.93274
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.777932	valid-rmse:0.80919
[20]	train-rmse:0.376792	valid-rmse:0.421943
[30]	train-rmse:0.348937	valid-rmse:0.394792
[39]	train-rmse:0.343305	valid-rmse:0.389489
Iteration No: 33 ended. Search finished for the next optimal point.
Time taken: 11.5275
Function value obtained: 0.3895
Current minimum: 0.3814
Iteration No: 34 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21883	valid-rmse:4.2372
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395799	valid-rmse:0.440293
[20]	train-rmse:0.344577	valid-rmse:0.391066
[30]	train-rmse:0.336463	valid-rmse:0.384766
[39]	train-rmse:0.333151	valid-rmse:0.382692
Iteration No: 34 ended. Search finished for the next optimal point.
Time taken: 16.4786
Function value obtained: 0.3827
Current minimum: 0.3814
Iteration No: 35 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.18180143057300549, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91495	valid-rmse:4.9325
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.751319	valid-rmse:0.781658
[20]	train-rmse:0.355179	valid-rmse:0.402365
[30]	train-rmse:0.336882	valid-rmse:0.385122
[39]	train-rmse:0.33314	valid-rmse:0.382267
Iteration No: 35 ended. Search finished for the next optimal point.
Time taken: 17.5337
Function value obtained: 0.3823
Current minimum: 0.3814
Iteration No: 36 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 47, 'eta': 0.15481691906904671, 'colsample_bytree': 0.4412185496472274, 'max_depth': 198, 'subsample': 0.97755342427047376, 'lambda': 4.0591662635941921, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.07749	valid-rmse:5.09526
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.02066	valid-rmse:1.04732
[20]	train-rmse:0.392034	valid-rmse:0.440242
[30]	train-rmse:0.332789	valid-rmse:0.387297
[39]	train-rmse:0.324994	valid-rmse:0.381763
Iteration No: 36 ended. Search finished for the next optimal point.
Time taken: 10.6266
Function value obtained: 0.3818
Current minimum: 0.3814
Iteration No: 37 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 178, 'eta': 0.1703771151528988, 'colsample_bytree': 0.40000000000000002, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98357	valid-rmse:5.00114
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.853304	valid-rmse:0.881561
[20]	train-rmse:0.368185	valid-rmse:0.415122
[30]	train-rmse:0.33852	valid-rmse:0.387662
[39]	train-rmse:0.333152	valid-rmse:0.38377
Iteration No: 37 ended. Search finished for the next optimal point.
Time taken: 8.4952
Function value obtained: 0.3838
Current minimum: 0.3814
Iteration No: 38 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.17008785493892481, 'colsample_bytree': 1.0, 'max_depth': 90, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98501	valid-rmse:5.00261
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.853567	valid-rmse:0.881691
[20]	train-rmse:0.367653	valid-rmse:0.413756
[30]	train-rmse:0.340009	valid-rmse:0.387383
[39]	train-rmse:0.335942	valid-rmse:0.38381
Iteration No: 38 ended. Search finished for the next optimal point.
Time taken: 15.3415
Function value obtained: 0.3838
Current minimum: 0.3814
Iteration No: 39 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 40, 'eta': 0.29604858879023416, 'colsample_bytree': 0.54031732707977109, 'max_depth': 190, 'subsample': 0.96193937534687646, 'lambda': 89.764059784632977, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2428	valid-rmse:4.26131
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.39705	valid-rmse:0.441831
[20]	train-rmse:0.343366	valid-rmse:0.391254
[30]	train-rmse:0.336036	valid-rmse:0.385297
[39]	train-rmse:0.332672	valid-rmse:0.382987
Iteration No: 39 ended. Search finished for the next optimal point.
Time taken: 11.3680
Function value obtained: 0.3830
Current minimum: 0.3814
Iteration No: 40 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 15, 'eta': 0.23865650111573139, 'colsample_bytree': 0.91879870638490879, 'max_depth': 197, 'subsample': 0.82488107270916677, 'lambda': 88.513421821220064, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.58298	valid-rmse:4.60121
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.495166	valid-rmse:0.53583
[20]	train-rmse:0.349209	valid-rmse:0.397375
[30]	train-rmse:0.3376	valid-rmse:0.386874
[39]	train-rmse:0.333818	valid-rmse:0.384335
Iteration No: 40 ended. Search finished for the next optimal point.
Time taken: 18.0331
Function value obtained: 0.3843
Current minimum: 0.3814
Iteration No: 41 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 199, 'eta': 0.25794482641680794, 'colsample_bytree': 0.42167304327872585, 'max_depth': 197, 'subsample': 0.89068476094339843, 'lambda': 88.214861526529546, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4688	valid-rmse:4.48722
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.456537	valid-rmse:0.497864
[20]	train-rmse:0.353749	valid-rmse:0.399144
[30]	train-rmse:0.341311	valid-rmse:0.388014
[39]	train-rmse:0.337349	valid-rmse:0.384695
Iteration No: 41 ended. Search finished for the next optimal point.
Time taken: 7.2840
Function value obtained: 0.3847
Current minimum: 0.3814
Iteration No: 42 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.24126683092459558, 'colsample_bytree': 0.66485987860236584, 'max_depth': 200, 'subsample': 0.90027288784048143, 'lambda': 40.540338535825818, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.5658	valid-rmse:4.58423
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.484825	valid-rmse:0.524733
[20]	train-rmse:0.350307	valid-rmse:0.396103
[30]	train-rmse:0.339085	valid-rmse:0.385944
[39]	train-rmse:0.334951	valid-rmse:0.382948
Iteration No: 42 ended. Search finished for the next optimal point.
Time taken: 10.5851
Function value obtained: 0.3829
Current minimum: 0.3814
Iteration No: 43 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.17762692318226966, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 54.646343302832477, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94381	valid-rmse:4.96199
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.810073	valid-rmse:0.840906
[20]	train-rmse:0.369348	valid-rmse:0.419143
[30]	train-rmse:0.332936	valid-rmse:0.388355
[39]	train-rmse:0.324468	valid-rmse:0.383342
Iteration No: 43 ended. Search finished for the next optimal point.
Time taken: 20.3690
Function value obtained: 0.3833
Current minimum: 0.3814
Iteration No: 44 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 27, 'eta': 0.18856767948620573, 'colsample_bytree': 0.69955801483323976, 'max_depth': 78, 'subsample': 0.97734566564588943, 'lambda': 89.217808298118527, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88015	valid-rmse:4.89837
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.732668	valid-rmse:0.76528
[20]	train-rmse:0.365803	valid-rmse:0.413739
[30]	train-rmse:0.337029	valid-rmse:0.388279
[39]	train-rmse:0.329008	valid-rmse:0.382931
Iteration No: 44 ended. Search finished for the next optimal point.
Time taken: 11.9989
Function value obtained: 0.3829
Current minimum: 0.3814
Iteration No: 45 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 32, 'eta': 0.24393381675713957, 'colsample_bytree': 0.95181281983011456, 'max_depth': 150, 'subsample': 0.99506283394000994, 'lambda': 87.170995732307048, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55112	valid-rmse:4.56936
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.47783	valid-rmse:0.519207
[20]	train-rmse:0.34257	valid-rmse:0.392918
[30]	train-rmse:0.330466	valid-rmse:0.384296
[39]	train-rmse:0.325686	valid-rmse:0.382388
Iteration No: 45 ended. Search finished for the next optimal point.
Time taken: 19.3765
Function value obtained: 0.3824
Current minimum: 0.3814
Iteration No: 46 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 150, 'eta': 0.17720488474881657, 'colsample_bytree': 1.0, 'max_depth': 118, 'subsample': 1.0, 'lambda': 29.609280641033624, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94553	valid-rmse:4.96351
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.809227	valid-rmse:0.839162
[20]	train-rmse:0.368657	valid-rmse:0.414581
[30]	train-rmse:0.33779	valid-rmse:0.385994
[39]	train-rmse:0.331763	valid-rmse:0.381487
Iteration No: 46 ended. Search finished for the next optimal point.
Time taken: 14.4407
Function value obtained: 0.3815
Current minimum: 0.3814
Iteration No: 47 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 13, 'eta': 0.19618625185118505, 'colsample_bytree': 0.51971940812044026, 'max_depth': 199, 'subsample': 0.82184321331753885, 'lambda': 86.439553212493294, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.83523	valid-rmse:4.8535
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.684803	valid-rmse:0.718896
[20]	train-rmse:0.363315	valid-rmse:0.411512
[30]	train-rmse:0.336945	valid-rmse:0.388916
[39]	train-rmse:0.329256	valid-rmse:0.384031
Iteration No: 47 ended. Search finished for the next optimal point.
Time taken: 10.0455
Function value obtained: 0.3840
Current minimum: 0.3814
Iteration No: 48 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 20, 'eta': 0.29929125804448542, 'colsample_bytree': 0.41897377002758734, 'max_depth': 191, 'subsample': 0.84901161598401487, 'lambda': 87.961354328465603, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22388	valid-rmse:4.2424
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.398788	valid-rmse:0.443599
[20]	train-rmse:0.346426	valid-rmse:0.393875
[30]	train-rmse:0.337015	valid-rmse:0.386305
[39]	train-rmse:0.333927	valid-rmse:0.384285
Iteration No: 48 ended. Search finished for the next optimal point.
Time taken: 9.2657
Function value obtained: 0.3843
Current minimum: 0.3814
Iteration No: 49 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 286, 'eta': 0.15687664212743641, 'colsample_bytree': 0.4016055479222152, 'max_depth': 19, 'subsample': 0.88080698020360693, 'lambda': 0.49572692542835028, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.06501	valid-rmse:5.08286
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.99465	valid-rmse:1.02084
[20]	train-rmse:0.393839	valid-rmse:0.438056
[30]	train-rmse:0.345206	valid-rmse:0.391991
[39]	train-rmse:0.338553	valid-rmse:0.385862
Iteration No: 49 ended. Search finished for the next optimal point.
Time taken: 6.3262
Function value obtained: 0.3859
Current minimum: 0.3814
Iteration No: 50 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 35, 'eta': 0.10404879696874483, 'colsample_bytree': 0.74108161367469361, 'max_depth': 191, 'subsample': 0.96296418543551854, 'lambda': 0.48023613107988539, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.37948	valid-rmse:5.39726
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.82871	valid-rmse:1.84895
[20]	train-rmse:0.692901	valid-rmse:0.726973
[30]	train-rmse:0.38936	valid-rmse:0.440853
[39]	train-rmse:0.335144	valid-rmse:0.39279
Iteration No: 50 ended. Search finished for the next optimal point.
Time taken: 15.7581
Function value obtained: 0.3928
Current minimum: 0.3814
Iteration No: 51 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 154, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21877	valid-rmse:4.23712
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391082	valid-rmse:0.435457
[20]	train-rmse:0.341855	valid-rmse:0.3894
[30]	train-rmse:0.332896	valid-rmse:0.382806
[39]	train-rmse:0.329519	valid-rmse:0.381509
Iteration No: 51 ended. Search finished for the next optimal point.
Time taken: 18.8852
Function value obtained: 0.3815
Current minimum: 0.3814
Iteration No: 52 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 210, 'eta': 0.17881053296269786, 'colsample_bytree': 1.0, 'max_depth': 125, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93285	valid-rmse:4.95042
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.774484	valid-rmse:0.804488
[20]	train-rmse:0.355289	valid-rmse:0.403531
[30]	train-rmse:0.335523	valid-rmse:0.385324
[39]	train-rmse:0.331948	valid-rmse:0.382781
Iteration No: 52 ended. Search finished for the next optimal point.
Time taken: 19.8657
Function value obtained: 0.3828
Current minimum: 0.3814
Iteration No: 53 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 23, 'eta': 0.26216600835724779, 'colsample_bytree': 0.56932716062045308, 'max_depth': 101, 'subsample': 0.99273213619936129, 'lambda': 85.466471885916278, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.44332	valid-rmse:4.46166
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.441342	valid-rmse:0.484055
[20]	train-rmse:0.34063	valid-rmse:0.391219
[30]	train-rmse:0.328919	valid-rmse:0.383918
[39]	train-rmse:0.324223	valid-rmse:0.382331
Iteration No: 53 ended. Search finished for the next optimal point.
Time taken: 12.8112
Function value obtained: 0.3823
Current minimum: 0.3814
Iteration No: 54 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.21510115778674543, 'colsample_bytree': 0.40000000000000002, 'max_depth': 132, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.7225	valid-rmse:4.74073
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.589144	valid-rmse:0.626251
[20]	train-rmse:0.358742	valid-rmse:0.407784
[30]	train-rmse:0.335843	valid-rmse:0.389621
[39]	train-rmse:0.327587	valid-rmse:0.384562
Iteration No: 54 ended. Search finished for the next optimal point.
Time taken: 9.2003
Function value obtained: 0.3846
Current minimum: 0.3814
Iteration No: 55 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 249, 'eta': 0.21589335421286832, 'colsample_bytree': 0.57800892725438868, 'max_depth': 12, 'subsample': 0.90634456430223731, 'lambda': 3.9526770769039543, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.71371	valid-rmse:4.73146
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.55713	valid-rmse:0.593641
[20]	train-rmse:0.349224	valid-rmse:0.395484
[30]	train-rmse:0.340942	valid-rmse:0.387503
[39]	train-rmse:0.338948	valid-rmse:0.385878
Iteration No: 55 ended. Search finished for the next optimal point.
Time taken: 5.7792
Function value obtained: 0.3859
Current minimum: 0.3814
Iteration No: 56 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 184, 'eta': 0.29731263143819886, 'colsample_bytree': 0.48390479303411926, 'max_depth': 200, 'subsample': 0.8344712596499918, 'lambda': 55.458606969383979, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.23425	valid-rmse:4.25283
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395818	valid-rmse:0.439893
[20]	train-rmse:0.343146	valid-rmse:0.39041
[30]	train-rmse:0.334772	valid-rmse:0.383848
[39]	train-rmse:0.331442	valid-rmse:0.381959
Iteration No: 56 ended. Search finished for the next optimal point.
Time taken: 9.4511
Function value obtained: 0.3820
Current minimum: 0.3814
Iteration No: 57 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 126, 'eta': 0.2016059867973119, 'colsample_bytree': 0.40000000000000002, 'max_depth': 134, 'subsample': 1.0, 'lambda': 50.285462311945274, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.80152	valid-rmse:4.81967
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.651359	valid-rmse:0.68578
[20]	train-rmse:0.362259	valid-rmse:0.408836
[30]	train-rmse:0.339377	valid-rmse:0.388025
[39]	train-rmse:0.332465	valid-rmse:0.3828
Iteration No: 57 ended. Search finished for the next optimal point.
Time taken: 7.3510
Function value obtained: 0.3828
Current minimum: 0.3814
Iteration No: 58 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 183, 'eta': 0.26235803323901863, 'colsample_bytree': 0.97701886085767975, 'max_depth': 140, 'subsample': 0.9432221898517541, 'lambda': 89.748762435588972, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.44217	valid-rmse:4.46052
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.440077	valid-rmse:0.482529
[20]	train-rmse:0.346279	valid-rmse:0.393132
[30]	train-rmse:0.335876	valid-rmse:0.384604
[39]	train-rmse:0.332022	valid-rmse:0.382126
Iteration No: 58 ended. Search finished for the next optimal point.
Time taken: 15.4455
Function value obtained: 0.3821
Current minimum: 0.3814
Iteration No: 59 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 297, 'eta': 0.19666853588893546, 'colsample_bytree': 0.67291542468574861, 'max_depth': 92, 'subsample': 0.91362009405039879, 'lambda': 36.231244097209192, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.83057	valid-rmse:4.84889
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.674172	valid-rmse:0.707345
[20]	train-rmse:0.361955	valid-rmse:0.407524
[30]	train-rmse:0.342483	valid-rmse:0.388999
[39]	train-rmse:0.336886	valid-rmse:0.384511
Iteration No: 59 ended. Search finished for the next optimal point.
Time taken: 9.4615
Function value obtained: 0.3845
Current minimum: 0.3814
Iteration No: 60 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 131, 'eta': 0.26698876760386747, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4145	valid-rmse:4.43277
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.431084	valid-rmse:0.474002
[20]	train-rmse:0.344238	valid-rmse:0.391979
[30]	train-rmse:0.333811	valid-rmse:0.384069
[39]	train-rmse:0.330078	valid-rmse:0.38232
Iteration No: 60 ended. Search finished for the next optimal point.
Time taken: 18.0860
Function value obtained: 0.3823
Current minimum: 0.3814
Iteration No: 61 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 296, 'eta': 0.29504744187706733, 'colsample_bytree': 0.44400145130469498, 'max_depth': 199, 'subsample': 0.87996974372783798, 'lambda': 36.895104978420022, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.24632	valid-rmse:4.2648
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.396724	valid-rmse:0.440332
[20]	train-rmse:0.345304	valid-rmse:0.391438
[30]	train-rmse:0.33708	valid-rmse:0.38486
[39]	train-rmse:0.333674	valid-rmse:0.382778
Iteration No: 61 ended. Search finished for the next optimal point.
Time taken: 8.1992
Function value obtained: 0.3828
Current minimum: 0.3814
Iteration No: 62 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 235, 'eta': 0.18547606467502453, 'colsample_bytree': 1.0, 'max_depth': 116, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89304	valid-rmse:4.91056
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.722606	valid-rmse:0.754016
[20]	train-rmse:0.351567	valid-rmse:0.399456
[30]	train-rmse:0.335425	valid-rmse:0.384472
[39]	train-rmse:0.332111	valid-rmse:0.382254
Iteration No: 62 ended. Search finished for the next optimal point.
Time taken: 19.8366
Function value obtained: 0.3823
Current minimum: 0.3814
Iteration No: 63 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 36, 'eta': 0.29184360764414452, 'colsample_bytree': 0.54216995948555102, 'max_depth': 91, 'subsample': 0.93743729890147998, 'lambda': 89.870820429780338, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.26785	valid-rmse:4.28635
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.401505	valid-rmse:0.446092
[20]	train-rmse:0.339093	valid-rmse:0.389441
[30]	train-rmse:0.329756	valid-rmse:0.383764
[39]	train-rmse:0.325757	valid-rmse:0.382478
Iteration No: 63 ended. Search finished for the next optimal point.
Time taken: 12.3834
Function value obtained: 0.3825
Current minimum: 0.3814
Iteration No: 64 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.1504044360649002, 'colsample_bytree': 0.5660737349270758, 'max_depth': 173, 'subsample': 0.98989857217142285, 'lambda': 3.1616890991135489, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.10367	valid-rmse:5.12148
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.0711	valid-rmse:1.09659
[20]	train-rmse:0.4064	valid-rmse:0.450344
[30]	train-rmse:0.344513	valid-rmse:0.391665
[39]	train-rmse:0.336835	valid-rmse:0.3846
Iteration No: 64 ended. Search finished for the next optimal point.
Time taken: 8.4236
Function value obtained: 0.3846
Current minimum: 0.3814
Iteration No: 65 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 278, 'eta': 0.29933246182075712, 'colsample_bytree': 0.97936898654377624, 'max_depth': 129, 'subsample': 0.85821029339045096, 'lambda': 84.491972216940894, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22297	valid-rmse:4.24133
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.396288	valid-rmse:0.440385
[20]	train-rmse:0.345707	valid-rmse:0.391472
[30]	train-rmse:0.337484	valid-rmse:0.385154
[39]	train-rmse:0.333619	valid-rmse:0.3825
Iteration No: 65 ended. Search finished for the next optimal point.
Time taken: 15.3450
Function value obtained: 0.3825
Current minimum: 0.3814
Iteration No: 66 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.29857838701191275, 'colsample_bytree': 0.99531685929999381, 'max_depth': 131, 'subsample': 0.93331546953635092, 'lambda': 83.421203621980808, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2272	valid-rmse:4.24555
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391837	valid-rmse:0.437163
[20]	train-rmse:0.345103	valid-rmse:0.392165
[30]	train-rmse:0.338445	valid-rmse:0.386647
[39]	train-rmse:0.336436	valid-rmse:0.385505
Iteration No: 66 ended. Search finished for the next optimal point.
Time taken: 22.8526
Function value obtained: 0.3855
Current minimum: 0.3814
Iteration No: 67 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 298, 'eta': 0.29696609612006486, 'colsample_bytree': 0.6044176846620517, 'max_depth': 199, 'subsample': 0.9028066814551241, 'lambda': 88.825534402193142, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.23758	valid-rmse:4.25611
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.400689	valid-rmse:0.444239
[20]	train-rmse:0.348684	valid-rmse:0.394069
[30]	train-rmse:0.340158	valid-rmse:0.386599
[39]	train-rmse:0.336801	valid-rmse:0.383871
Iteration No: 67 ended. Search finished for the next optimal point.
Time taken: 9.6636
Function value obtained: 0.3839
Current minimum: 0.3814
Iteration No: 68 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.2990473743419223, 'colsample_bytree': 0.49164556157268585, 'max_depth': 130, 'subsample': 0.92257839764351934, 'lambda': 89.897718315007779, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22518	valid-rmse:4.2437
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.399929	valid-rmse:0.443865
[20]	train-rmse:0.348996	valid-rmse:0.394832
[30]	train-rmse:0.341733	valid-rmse:0.388177
[39]	train-rmse:0.338652	valid-rmse:0.385793
Iteration No: 68 ended. Search finished for the next optimal point.
Time taken: 8.6339
Function value obtained: 0.3858
Current minimum: 0.3814
Iteration No: 69 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26864124468412676, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 42.108060898444357, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.40265	valid-rmse:4.42101
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.422956	valid-rmse:0.466249
[20]	train-rmse:0.344161	valid-rmse:0.391073
[30]	train-rmse:0.336025	valid-rmse:0.384441
[39]	train-rmse:0.332571	valid-rmse:0.382348
Iteration No: 69 ended. Search finished for the next optimal point.
Time taken: 17.5914
Function value obtained: 0.3823
Current minimum: 0.3814
Iteration No: 70 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.2857156103203472, 'colsample_bytree': 0.40426281460146696, 'max_depth': 145, 'subsample': 0.816308935918447, 'lambda': 2.7163740740626343, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.29844	valid-rmse:4.31626
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.39367	valid-rmse:0.43754
[20]	train-rmse:0.345172	valid-rmse:0.391641
[30]	train-rmse:0.33813	valid-rmse:0.386024
[39]	train-rmse:0.335004	valid-rmse:0.384277
Iteration No: 70 ended. Search finished for the next optimal point.
Time taken: 8.5360
Function value obtained: 0.3843
Current minimum: 0.3814
Iteration No: 71 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 290, 'eta': 0.19578837120085688, 'colsample_bytree': 0.6741231637158257, 'max_depth': 198, 'subsample': 0.98675801128944651, 'lambda': 47.358972644739559, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.83605	valid-rmse:4.85436
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.680812	valid-rmse:0.713769
[20]	train-rmse:0.362841	valid-rmse:0.408275
[30]	train-rmse:0.342165	valid-rmse:0.388832
[39]	train-rmse:0.336103	valid-rmse:0.38394
Iteration No: 71 ended. Search finished for the next optimal point.
Time taken: 9.5068
Function value obtained: 0.3839
Current minimum: 0.3814
Iteration No: 72 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 18, 'eta': 0.17395081280357227, 'colsample_bytree': 0.83537762306238217, 'max_depth': 29, 'subsample': 0.88246964753792301, 'lambda': 87.475442003962485, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96706	valid-rmse:4.98526
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.846819	valid-rmse:0.877248
[20]	train-rmse:0.380545	valid-rmse:0.428092
[30]	train-rmse:0.340282	valid-rmse:0.391703
[39]	train-rmse:0.330581	valid-rmse:0.38449
Iteration No: 72 ended. Search finished for the next optimal point.
Time taken: 13.2008
Function value obtained: 0.3845
Current minimum: 0.3814
Iteration No: 73 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.21389364920190232, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.72347	valid-rmse:4.74095
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.554389	valid-rmse:0.591096
[20]	train-rmse:0.343502	valid-rmse:0.391267
[30]	train-rmse:0.335116	valid-rmse:0.383917
[39]	train-rmse:0.332189	valid-rmse:0.382011
Iteration No: 73 ended. Search finished for the next optimal point.
Time taken: 19.8637
Function value obtained: 0.3820
Current minimum: 0.3814
Iteration No: 74 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.17357299544570348, 'colsample_bytree': 0.52794084126148122, 'max_depth': 118, 'subsample': 0.86049536779691693, 'lambda': 55.583235155824688, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96852	valid-rmse:4.98675
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.848121	valid-rmse:0.878268
[20]	train-rmse:0.37932	valid-rmse:0.426982
[30]	train-rmse:0.33762	valid-rmse:0.390327
[39]	train-rmse:0.328111	valid-rmse:0.384021
Iteration No: 74 ended. Search finished for the next optimal point.
Time taken: 10.6521
Function value obtained: 0.3840
Current minimum: 0.3814
Iteration No: 75 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 11, 'eta': 0.15055162031428274, 'colsample_bytree': 0.67511740385121688, 'max_depth': 198, 'subsample': 0.85867461617702212, 'lambda': 5.1189346493396659, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.10292	valid-rmse:5.12078
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.07047	valid-rmse:1.09658
[20]	train-rmse:0.402739	valid-rmse:0.453081
[30]	train-rmse:0.33166	valid-rmse:0.392523
[39]	train-rmse:0.32218	valid-rmse:0.386759
Iteration No: 75 ended. Search finished for the next optimal point.
Time taken: 17.9492
Function value obtained: 0.3868
Current minimum: 0.3814
Iteration No: 76 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21877	valid-rmse:4.23712
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391152	valid-rmse:0.435488
[20]	train-rmse:0.340743	valid-rmse:0.388193
[30]	train-rmse:0.33315	valid-rmse:0.383335
[39]	train-rmse:0.329752	valid-rmse:0.381751
Iteration No: 76 ended. Search finished for the next optimal point.
Time taken: 19.6222
Function value obtained: 0.3818
Current minimum: 0.3814
Iteration No: 77 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 291, 'eta': 0.10022647608198934, 'colsample_bytree': 0.99162972506427249, 'max_depth': 176, 'subsample': 0.81481064568280337, 'lambda': 0.45639626645420861, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.40223	valid-rmse:5.42004
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.91378	valid-rmse:1.93353
[20]	train-rmse:0.74733	valid-rmse:0.777925
[30]	train-rmse:0.418178	valid-rmse:0.461392
[39]	train-rmse:0.354868	valid-rmse:0.401713
Iteration No: 77 ended. Search finished for the next optimal point.
Time taken: 11.8093
Function value obtained: 0.4017
Current minimum: 0.3814
Iteration No: 78 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.17174873755073253, 'colsample_bytree': 0.64882198339307573, 'max_depth': 50, 'subsample': 0.98057761049619985, 'lambda': 38.732985256484163, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97856	valid-rmse:4.99679
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.860472	valid-rmse:0.889873
[20]	train-rmse:0.379155	valid-rmse:0.424692
[30]	train-rmse:0.341582	valid-rmse:0.389446
[39]	train-rmse:0.333655	valid-rmse:0.382688
Iteration No: 78 ended. Search finished for the next optimal point.
Time taken: 9.1680
Function value obtained: 0.3827
Current minimum: 0.3814
Iteration No: 79 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.18599765763665849, 'colsample_bytree': 0.52282356042877143, 'max_depth': 13, 'subsample': 0.84917491770733866, 'lambda': 2.2208360711534105, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89151	valid-rmse:4.90928
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.729131	valid-rmse:0.760116
[20]	train-rmse:0.360076	valid-rmse:0.405627
[30]	train-rmse:0.342995	valid-rmse:0.38894
[39]	train-rmse:0.340114	valid-rmse:0.386448
Iteration No: 79 ended. Search finished for the next optimal point.
Time taken: 5.9140
Function value obtained: 0.3864
Current minimum: 0.3814
Iteration No: 80 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 21, 'eta': 0.22831975567868304, 'colsample_bytree': 0.99548044511003009, 'max_depth': 34, 'subsample': 0.95199544123175628, 'lambda': 87.592306510454549, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.64394	valid-rmse:4.66214
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.526572	valid-rmse:0.565751
[20]	train-rmse:0.346427	valid-rmse:0.396524
[30]	train-rmse:0.33123	valid-rmse:0.385331
[39]	train-rmse:0.32591	valid-rmse:0.382856
Iteration No: 80 ended. Search finished for the next optimal point.
Time taken: 17.6706
Function value obtained: 0.3829
Current minimum: 0.3814
Iteration No: 81 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 151, 'eta': 0.19356565269031262, 'colsample_bytree': 1.0, 'max_depth': 121, 'subsample': 1.0, 'lambda': 41.459204986006981, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8487	valid-rmse:4.86691
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.69101	valid-rmse:0.72399
[20]	train-rmse:0.358392	valid-rmse:0.405178
[30]	train-rmse:0.336712	valid-rmse:0.385416
[39]	train-rmse:0.330947	valid-rmse:0.38129
Iteration No: 81 ended. Search finished for the next optimal point.
Time taken: 14.7959
Function value obtained: 0.3813
Current minimum: 0.3813
Iteration No: 82 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.21085364644626681, 'colsample_bytree': 1.0, 'max_depth': 109, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.74754	valid-rmse:4.76572
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.600275	valid-rmse:0.637031
[20]	train-rmse:0.351034	valid-rmse:0.401918
[30]	train-rmse:0.331119	valid-rmse:0.386195
[39]	train-rmse:0.324422	valid-rmse:0.382888
Iteration No: 82 ended. Search finished for the next optimal point.
Time taken: 20.6388
Function value obtained: 0.3829
Current minimum: 0.3813
Iteration No: 83 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.152676534046681, 'colsample_bytree': 0.41943174268612393, 'max_depth': 195, 'subsample': 0.95483258993287357, 'lambda': 2.085698182769617, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.09001	valid-rmse:5.10782
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.04513	valid-rmse:1.07103
[20]	train-rmse:0.402973	valid-rmse:0.447163
[30]	train-rmse:0.346527	valid-rmse:0.39339
[39]	train-rmse:0.340323	valid-rmse:0.387345
Iteration No: 83 ended. Search finished for the next optimal point.
Time taken: 7.4205
Function value obtained: 0.3873
Current minimum: 0.3813
Iteration No: 84 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 152, 'eta': 0.18420933461585606, 'colsample_bytree': 0.61269450839913042, 'max_depth': 15, 'subsample': 0.93239313598383244, 'lambda': 0.44476176068262718, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90155	valid-rmse:4.9192
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.733515	valid-rmse:0.764948
[20]	train-rmse:0.351453	valid-rmse:0.399643
[30]	train-rmse:0.336044	valid-rmse:0.384759
[39]	train-rmse:0.334145	valid-rmse:0.383202
Iteration No: 84 ended. Search finished for the next optimal point.
Time taken: 7.6892
Function value obtained: 0.3832
Current minimum: 0.3813
Iteration No: 85 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 11, 'eta': 0.29930263368860732, 'colsample_bytree': 0.46100766081010286, 'max_depth': 180, 'subsample': 0.85330530084725187, 'lambda': 88.451112565769876, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22379	valid-rmse:4.24231
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.398661	valid-rmse:0.444091
[20]	train-rmse:0.339605	valid-rmse:0.390943
[30]	train-rmse:0.328855	valid-rmse:0.384564
[39]	train-rmse:0.324297	valid-rmse:0.382693
Iteration No: 85 ended. Search finished for the next optimal point.
Time taken: 12.1537
Function value obtained: 0.3827
Current minimum: 0.3813
Iteration No: 86 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 209, 'eta': 0.17767644132533464, 'colsample_bytree': 0.40000000000000002, 'max_depth': 107, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94005	valid-rmse:4.9576
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.789054	valid-rmse:0.818648
[20]	train-rmse:0.362371	valid-rmse:0.409202
[30]	train-rmse:0.3385	valid-rmse:0.387033
[39]	train-rmse:0.333416	valid-rmse:0.383303
Iteration No: 86 ended. Search finished for the next optimal point.
Time taken: 8.4417
Function value obtained: 0.3833
Current minimum: 0.3813
Iteration No: 87 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 121, 'eta': 0.27231424083900346, 'colsample_bytree': 1.0, 'max_depth': 162, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.38291	valid-rmse:4.4012
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.421964	valid-rmse:0.465627
[20]	train-rmse:0.342477	valid-rmse:0.390852
[30]	train-rmse:0.333075	valid-rmse:0.383775
[39]	train-rmse:0.329581	valid-rmse:0.382348
Iteration No: 87 ended. Search finished for the next optimal point.
Time taken: 18.1655
Function value obtained: 0.3823
Current minimum: 0.3813
Iteration No: 88 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26761107925645189, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 39.097085470738364, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.40864	valid-rmse:4.42699
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.423298	valid-rmse:0.466021
[20]	train-rmse:0.343773	valid-rmse:0.390178
[30]	train-rmse:0.33541	valid-rmse:0.383601
[39]	train-rmse:0.332223	valid-rmse:0.381679
Iteration No: 88 ended. Search finished for the next optimal point.
Time taken: 16.3545
Function value obtained: 0.3817
Current minimum: 0.3813
Iteration No: 89 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.21864774538708331, 'colsample_bytree': 0.52792432789585531, 'max_depth': 96, 'subsample': 0.83048843229568081, 'lambda': 89.633847346908325, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.70204	valid-rmse:4.72037
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.570743	valid-rmse:0.607791
[20]	train-rmse:0.357574	valid-rmse:0.40355
[30]	train-rmse:0.340856	valid-rmse:0.388302
[39]	train-rmse:0.334807	valid-rmse:0.383512
Iteration No: 89 ended. Search finished for the next optimal point.
Time taken: 8.0283
Function value obtained: 0.3835
Current minimum: 0.3813
Iteration No: 90 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 144, 'eta': 0.19171539455638295, 'colsample_bytree': 1.0, 'max_depth': 101, 'subsample': 1.0, 'lambda': 42.005810230261204, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85972	valid-rmse:4.87792
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.703189	valid-rmse:0.735798
[20]	train-rmse:0.359325	valid-rmse:0.405991
[30]	train-rmse:0.33705	valid-rmse:0.385703
[39]	train-rmse:0.330873	valid-rmse:0.381286
Iteration No: 90 ended. Search finished for the next optimal point.
Time taken: 15.4342
Function value obtained: 0.3813
Current minimum: 0.3813
Iteration No: 91 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 164, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21879	valid-rmse:4.23714
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391264	valid-rmse:0.435692
[20]	train-rmse:0.341903	valid-rmse:0.389277
[30]	train-rmse:0.333828	valid-rmse:0.383694
[39]	train-rmse:0.330335	valid-rmse:0.381856
Iteration No: 91 ended. Search finished for the next optimal point.
Time taken: 18.6282
Function value obtained: 0.3819
Current minimum: 0.3813
Iteration No: 92 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 118, 'eta': 0.18698404202714425, 'colsample_bytree': 0.88215896324412801, 'max_depth': 15, 'subsample': 0.90221206166894063, 'lambda': 88.861577707392968, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8897	valid-rmse:4.90793
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.744856	valid-rmse:0.77669
[20]	train-rmse:0.369216	valid-rmse:0.41526
[30]	train-rmse:0.343075	valid-rmse:0.390397
[39]	train-rmse:0.337591	valid-rmse:0.385568
Iteration No: 92 ended. Search finished for the next optimal point.
Time taken: 8.6291
Function value obtained: 0.3856
Current minimum: 0.3813
Iteration No: 93 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 221, 'eta': 0.18185588490282287, 'colsample_bytree': 1.0, 'max_depth': 108, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91466	valid-rmse:4.93222
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.750207	valid-rmse:0.780923
[20]	train-rmse:0.352979	valid-rmse:0.401161
[30]	train-rmse:0.334892	valid-rmse:0.384543
[39]	train-rmse:0.3316	valid-rmse:0.38238
Iteration No: 93 ended. Search finished for the next optimal point.
Time taken: 19.4645
Function value obtained: 0.3824
Current minimum: 0.3813
Iteration No: 94 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 129, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 166, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21879	valid-rmse:4.23714
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391471	valid-rmse:0.43617
[20]	train-rmse:0.341068	valid-rmse:0.389392
[30]	train-rmse:0.332625	valid-rmse:0.383489
[39]	train-rmse:0.329371	valid-rmse:0.382298
Iteration No: 94 ended. Search finished for the next optimal point.
Time taken: 19.4176
Function value obtained: 0.3823
Current minimum: 0.3813
Iteration No: 95 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 288, 'eta': 0.20966848548151137, 'colsample_bytree': 0.42192980030379534, 'max_depth': 186, 'subsample': 0.85687861402830334, 'lambda': 89.873295899564908, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.75522	valid-rmse:4.77352
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.614916	valid-rmse:0.650519
[20]	train-rmse:0.366704	valid-rmse:0.411815
[30]	train-rmse:0.345883	valid-rmse:0.392193
[39]	train-rmse:0.339415	valid-rmse:0.386466
Iteration No: 95 ended. Search finished for the next optimal point.
Time taken: 6.5316
Function value obtained: 0.3865
Current minimum: 0.3813
Iteration No: 96 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 115, 'eta': 0.24358946065857431, 'colsample_bytree': 0.40000000000000002, 'max_depth': 156, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55351	valid-rmse:4.57179
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.489796	valid-rmse:0.530428
[20]	train-rmse:0.353516	valid-rmse:0.400506
[30]	train-rmse:0.337792	valid-rmse:0.387134
[39]	train-rmse:0.331756	valid-rmse:0.38296
Iteration No: 96 ended. Search finished for the next optimal point.
Time taken: 7.5577
Function value obtained: 0.3830
Current minimum: 0.3813
Iteration No: 97 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 292, 'eta': 0.23754599076886854, 'colsample_bytree': 0.9522246252988652, 'max_depth': 103, 'subsample': 0.99351011218964769, 'lambda': 11.315887736342104, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.58535	valid-rmse:4.60325
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.481069	valid-rmse:0.520975
[20]	train-rmse:0.344381	valid-rmse:0.391395
[30]	train-rmse:0.335621	valid-rmse:0.383755
[39]	train-rmse:0.332345	valid-rmse:0.381539
Iteration No: 97 ended. Search finished for the next optimal point.
Time taken: 16.2922
Function value obtained: 0.3815
Current minimum: 0.3813
Iteration No: 98 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 291, 'eta': 0.26034115468735514, 'colsample_bytree': 0.87237094146812999, 'max_depth': 199, 'subsample': 0.8093864453599674, 'lambda': 86.660667098724744, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.45488	valid-rmse:4.47327
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.447959	valid-rmse:0.489755
[20]	train-rmse:0.351268	valid-rmse:0.397061
[30]	train-rmse:0.340187	valid-rmse:0.386722
[39]	train-rmse:0.335597	valid-rmse:0.383277
Iteration No: 98 ended. Search finished for the next optimal point.
Time taken: 11.7797
Function value obtained: 0.3833
Current minimum: 0.3813
Iteration No: 99 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 202, 'eta': 0.29803438405591132, 'colsample_bytree': 0.77725806223062732, 'max_depth': 130, 'subsample': 0.99862902245174467, 'lambda': 49.107777911354184, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22908	valid-rmse:4.24769
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.390636	valid-rmse:0.435299
[20]	train-rmse:0.341338	valid-rmse:0.389256
[30]	train-rmse:0.333443	valid-rmse:0.383683
[39]	train-rmse:0.330227	valid-rmse:0.382129
Iteration No: 99 ended. Search finished for the next optimal point.
Time taken: 15.4084
Function value obtained: 0.3821
Current minimum: 0.3813
Iteration No: 100 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 299, 'eta': 0.29967127819294681, 'colsample_bytree': 0.46884110096084203, 'max_depth': 199, 'subsample': 0.83534203409052288, 'lambda': 63.98370736981591, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22067	valid-rmse:4.23925
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.398764	valid-rmse:0.442538
[20]	train-rmse:0.347525	valid-rmse:0.393265
[30]	train-rmse:0.339041	valid-rmse:0.386276
[39]	train-rmse:0.334955	valid-rmse:0.383461
Iteration No: 100 ended. Search finished for the next optimal point.
Time taken: 8.7601
Function value obtained: 0.3835
Current minimum: 0.3813
Iteration No: 101 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 15, 'eta': 0.18441693119459596, 'colsample_bytree': 0.45133035796375282, 'max_depth': 12, 'subsample': 0.90418111368999055, 'lambda': 89.74074873195228, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90498	valid-rmse:4.92323
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.765389	valid-rmse:0.797507
[20]	train-rmse:0.375664	valid-rmse:0.422235
[30]	train-rmse:0.344983	valid-rmse:0.393638
[39]	train-rmse:0.338489	valid-rmse:0.388022
Iteration No: 101 ended. Search finished for the next optimal point.
Time taken: 5.6707
Function value obtained: 0.3880
Current minimum: 0.3813
Iteration No: 102 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 296, 'eta': 0.16527830611427022, 'colsample_bytree': 0.63059752327826202, 'max_depth': 197, 'subsample': 0.90137804676862188, 'lambda': 0.20679454941408232, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01611	valid-rmse:5.03392
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.900972	valid-rmse:0.928369
[20]	train-rmse:0.374357	valid-rmse:0.419895
[30]	train-rmse:0.34104	valid-rmse:0.388317
[39]	train-rmse:0.336188	valid-rmse:0.384163
Iteration No: 102 ended. Search finished for the next optimal point.
Time taken: 10.7622
Function value obtained: 0.3842
Current minimum: 0.3813
Iteration No: 103 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 11, 'eta': 0.19197181817236683, 'colsample_bytree': 0.86708069288674294, 'max_depth': 15, 'subsample': 0.95405964046893887, 'lambda': 3.7727726838508246, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85591	valid-rmse:4.87368
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.68524	valid-rmse:0.719672
[20]	train-rmse:0.344749	valid-rmse:0.400061
[30]	train-rmse:0.329599	valid-rmse:0.387566
[39]	train-rmse:0.326946	valid-rmse:0.386126
Iteration No: 103 ended. Search finished for the next optimal point.
Time taken: 10.6446
Function value obtained: 0.3861
Current minimum: 0.3813
Iteration No: 104 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.19830849691843577, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.81664	valid-rmse:4.83418
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.639292	valid-rmse:0.672433
[20]	train-rmse:0.350237	valid-rmse:0.396898
[30]	train-rmse:0.338479	valid-rmse:0.385783
[39]	train-rmse:0.335639	valid-rmse:0.383685
Iteration No: 104 ended. Search finished for the next optimal point.
Time taken: 16.6719
Function value obtained: 0.3837
Current minimum: 0.3813
Iteration No: 105 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 295, 'eta': 0.26404735515953115, 'colsample_bytree': 0.69792459359009884, 'max_depth': 120, 'subsample': 0.98777956155940017, 'lambda': 84.150241245019799, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.43218	valid-rmse:4.45058
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.439257	valid-rmse:0.481286
[20]	train-rmse:0.348515	valid-rmse:0.394433
[30]	train-rmse:0.338284	valid-rmse:0.385497
[39]	train-rmse:0.333968	valid-rmse:0.382419
Iteration No: 105 ended. Search finished for the next optimal point.
Time taken: 11.0693
Function value obtained: 0.3824
Current minimum: 0.3813
Iteration No: 106 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 92, 'eta': 0.20055089218872041, 'colsample_bytree': 0.93979049576459328, 'max_depth': 9, 'subsample': 0.99895632332841955, 'lambda': 77.282855903537111, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8084	valid-rmse:4.82655
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.653919	valid-rmse:0.688346
[20]	train-rmse:0.364285	valid-rmse:0.410387
[30]	train-rmse:0.348593	valid-rmse:0.395064
[39]	train-rmse:0.344017	valid-rmse:0.390913
Iteration No: 106 ended. Search finished for the next optimal point.
Time taken: 6.7000
Function value obtained: 0.3909
Current minimum: 0.3813
Iteration No: 107 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 276, 'eta': 0.24781956088022833, 'colsample_bytree': 0.92709766552430972, 'max_depth': 77, 'subsample': 0.99749202632448886, 'lambda': 0.60111161768355958, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.5221	valid-rmse:4.53958
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.440188	valid-rmse:0.482009
[20]	train-rmse:0.338418	valid-rmse:0.386417
[30]	train-rmse:0.333388	valid-rmse:0.382771
[39]	train-rmse:0.331217	valid-rmse:0.381959
Iteration No: 107 ended. Search finished for the next optimal point.
Time taken: 20.2209
Function value obtained: 0.3820
Current minimum: 0.3813
Iteration No: 108 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.25557676364935644, 'colsample_bytree': 1.0, 'max_depth': 159, 'subsample': 1.0, 'lambda': 34.839203482049264, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.47991	valid-rmse:4.49824
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.444547	valid-rmse:0.486466
[20]	train-rmse:0.344836	valid-rmse:0.391152
[30]	train-rmse:0.33573	valid-rmse:0.383645
[39]	train-rmse:0.332818	valid-rmse:0.381891
Iteration No: 108 ended. Search finished for the next optimal point.
Time taken: 16.5979
Function value obtained: 0.3819
Current minimum: 0.3813
Iteration No: 109 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.27837423280981088, 'colsample_bytree': 0.40000000000000002, 'max_depth': 156, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.34724	valid-rmse:4.3656
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.4232	valid-rmse:0.466568
[20]	train-rmse:0.349184	valid-rmse:0.39668
[30]	train-rmse:0.336729	valid-rmse:0.386671
[39]	train-rmse:0.33168	valid-rmse:0.383362
Iteration No: 109 ended. Search finished for the next optimal point.
Time taken: 7.9050
Function value obtained: 0.3834
Current minimum: 0.3813
Iteration No: 110 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 299, 'eta': 0.19795230863170538, 'colsample_bytree': 0.91322675444078316, 'max_depth': 109, 'subsample': 0.95647374537969965, 'lambda': 89.172593308504247, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.82422	valid-rmse:4.84238
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.672977	valid-rmse:0.706682
[20]	train-rmse:0.364339	valid-rmse:0.410118
[30]	train-rmse:0.34305	valid-rmse:0.389684
[39]	train-rmse:0.336741	valid-rmse:0.384397
Iteration No: 110 ended. Search finished for the next optimal point.
Time taken: 11.2407
Function value obtained: 0.3844
Current minimum: 0.3813
Iteration No: 111 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 15, 'eta': 0.15191727528788096, 'colsample_bytree': 0.47257719157501554, 'max_depth': 107, 'subsample': 0.9206643159014728, 'lambda': 3.6830409436095088, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.0948	valid-rmse:5.11257
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.05321	valid-rmse:1.07928
[20]	train-rmse:0.396995	valid-rmse:0.446486
[30]	train-rmse:0.329625	valid-rmse:0.38936
[39]	train-rmse:0.320968	valid-rmse:0.384229
Iteration No: 111 ended. Search finished for the next optimal point.
Time taken: 14.8120
Function value obtained: 0.3842
Current minimum: 0.3813
Iteration No: 112 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 17, 'eta': 0.15870407655941079, 'colsample_bytree': 0.7696956107806423, 'max_depth': 81, 'subsample': 0.97742820887029325, 'lambda': 88.325412061150487, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.05742	valid-rmse:5.0756
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.994669	valid-rmse:1.02265
[20]	train-rmse:0.40411	valid-rmse:0.450227
[30]	train-rmse:0.344629	valid-rmse:0.395644
[39]	train-rmse:0.332632	valid-rmse:0.386158
Iteration No: 112 ended. Search finished for the next optimal point.
Time taken: 12.5051
Function value obtained: 0.3862
Current minimum: 0.3813
Iteration No: 113 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.24134782045426775, 'colsample_bytree': 1.0, 'max_depth': 153, 'subsample': 1.0, 'lambda': 36.074434609246559, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.56451	valid-rmse:4.58281
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.479072	valid-rmse:0.519279
[20]	train-rmse:0.34688	valid-rmse:0.393316
[30]	train-rmse:0.337158	valid-rmse:0.384875
[39]	train-rmse:0.332791	valid-rmse:0.381802
Iteration No: 113 ended. Search finished for the next optimal point.
Time taken: 15.8792
Function value obtained: 0.3818
Current minimum: 0.3813
Iteration No: 114 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 292, 'eta': 0.29988883328732407, 'colsample_bytree': 0.46076948240448018, 'max_depth': 103, 'subsample': 0.83383698957963626, 'lambda': 0.45554297465680071, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21243	valid-rmse:4.23002
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.374799	valid-rmse:0.420102
[20]	train-rmse:0.340793	valid-rmse:0.387804
[30]	train-rmse:0.336033	valid-rmse:0.384372
[39]	train-rmse:0.333645	valid-rmse:0.383258
Iteration No: 114 ended. Search finished for the next optimal point.
Time taken: 11.6511
Function value obtained: 0.3833
Current minimum: 0.3813
Iteration No: 115 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.17091628810016068, 'colsample_bytree': 0.73355038473526024, 'max_depth': 196, 'subsample': 0.88674801126923419, 'lambda': 84.970467639226015, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98502	valid-rmse:5.00326
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.874803	valid-rmse:0.904345
[20]	train-rmse:0.387069	valid-rmse:0.432025
[30]	train-rmse:0.346554	valid-rmse:0.393454
[39]	train-rmse:0.337775	valid-rmse:0.385888
Iteration No: 115 ended. Search finished for the next optimal point.
Time taken: 9.6603
Function value obtained: 0.3859
Current minimum: 0.3813
Iteration No: 116 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 296, 'eta': 0.28414077970862439, 'colsample_bytree': 0.48412515654306676, 'max_depth': 129, 'subsample': 0.98502046235630736, 'lambda': 0.74013032621325603, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.30627	valid-rmse:4.32403
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.387808	valid-rmse:0.432463
[20]	train-rmse:0.343457	valid-rmse:0.389618
[30]	train-rmse:0.339252	valid-rmse:0.38633
[39]	train-rmse:0.337591	valid-rmse:0.384999
Iteration No: 116 ended. Search finished for the next optimal point.
Time taken: 10.4126
Function value obtained: 0.3850
Current minimum: 0.3813
Iteration No: 117 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 274, 'eta': 0.29714325777767758, 'colsample_bytree': 0.44295236102035229, 'max_depth': 103, 'subsample': 0.86208067857830173, 'lambda': 89.119547082726015, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2366	valid-rmse:4.25514
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.406154	valid-rmse:0.449633
[20]	train-rmse:0.349722	valid-rmse:0.395749
[30]	train-rmse:0.339433	valid-rmse:0.38698
[39]	train-rmse:0.335072	valid-rmse:0.383644
Iteration No: 117 ended. Search finished for the next optimal point.
Time taken: 8.7438
Function value obtained: 0.3836
Current minimum: 0.3813
Iteration No: 118 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 162, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 153, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21877	valid-rmse:4.23712
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391395	valid-rmse:0.435749
[20]	train-rmse:0.341306	valid-rmse:0.388363
[30]	train-rmse:0.333748	valid-rmse:0.383211
[39]	train-rmse:0.330355	valid-rmse:0.381498
Iteration No: 118 ended. Search finished for the next optimal point.
Time taken: 19.4425
Function value obtained: 0.3815
Current minimum: 0.3813
Iteration No: 119 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 39, 'eta': 0.29852316370926174, 'colsample_bytree': 0.41639142744348723, 'max_depth': 106, 'subsample': 0.94286479369217069, 'lambda': 89.945924908355934, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22824	valid-rmse:4.24676
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.398583	valid-rmse:0.443616
[20]	train-rmse:0.341347	valid-rmse:0.391352
[30]	train-rmse:0.330324	valid-rmse:0.384049
[39]	train-rmse:0.326211	valid-rmse:0.382599
Iteration No: 119 ended. Search finished for the next optimal point.
Time taken: 10.6777
Function value obtained: 0.3826
Current minimum: 0.3813
Iteration No: 120 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 19, 'eta': 0.21297542633259958, 'colsample_bytree': 0.4498330203615466, 'max_depth': 200, 'subsample': 0.9245803914719295, 'lambda': 85.62013457746886, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.73536	valid-rmse:4.75366
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.594935	valid-rmse:0.631788
[20]	train-rmse:0.355932	valid-rmse:0.404733
[30]	train-rmse:0.335175	valid-rmse:0.387646
[39]	train-rmse:0.327936	valid-rmse:0.383341
Iteration No: 120 ended. Search finished for the next optimal point.
Time taken: 10.2221
Function value obtained: 0.3833
Current minimum: 0.3813
Iteration No: 121 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 206, 'eta': 0.18059791415423759, 'colsample_bytree': 1.0, 'max_depth': 73, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92219	valid-rmse:4.93974
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.759812	valid-rmse:0.79054
[20]	train-rmse:0.353949	valid-rmse:0.402466
[30]	train-rmse:0.33536	valid-rmse:0.385103
[39]	train-rmse:0.331724	valid-rmse:0.382486
Iteration No: 121 ended. Search finished for the next optimal point.
Time taken: 20.3940
Function value obtained: 0.3825
Current minimum: 0.3813
Iteration No: 122 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.27477000593891499, 'colsample_bytree': 0.40000000000000002, 'max_depth': 155, 'subsample': 1.0, 'lambda': 40.271656327630488, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.36658	valid-rmse:4.38489
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.422824	valid-rmse:0.465321
[20]	train-rmse:0.349833	valid-rmse:0.395503
[30]	train-rmse:0.33914	valid-rmse:0.386734
[39]	train-rmse:0.334848	valid-rmse:0.383962
Iteration No: 122 ended. Search finished for the next optimal point.
Time taken: 7.9761
Function value obtained: 0.3840
Current minimum: 0.3813
Iteration No: 123 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.1970234442849918, 'colsample_bytree': 1.0, 'max_depth': 92, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.82412	valid-rmse:4.84163
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.645876	valid-rmse:0.679152
[20]	train-rmse:0.348229	valid-rmse:0.395658
[30]	train-rmse:0.336021	valid-rmse:0.384719
[39]	train-rmse:0.332912	valid-rmse:0.382543
Iteration No: 123 ended. Search finished for the next optimal point.
Time taken: 18.7379
Function value obtained: 0.3825
Current minimum: 0.3813
Iteration No: 124 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 126, 'eta': 0.22660691247048467, 'colsample_bytree': 1.0, 'max_depth': 139, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.65405	valid-rmse:4.67225
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.533511	valid-rmse:0.571857
[20]	train-rmse:0.350179	valid-rmse:0.397339
[30]	train-rmse:0.336033	valid-rmse:0.385279
[39]	train-rmse:0.330339	valid-rmse:0.381356
Iteration No: 124 ended. Search finished for the next optimal point.
Time taken: 16.0947
Function value obtained: 0.3814
Current minimum: 0.3813
Iteration No: 125 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 160, 'subsample': 1.0, 'lambda': 48.768495095863607, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21679	valid-rmse:4.23524
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.388845	valid-rmse:0.433393
[20]	train-rmse:0.342333	valid-rmse:0.389227
[30]	train-rmse:0.335408	valid-rmse:0.384214
[39]	train-rmse:0.332306	valid-rmse:0.382418
Iteration No: 125 ended. Search finished for the next optimal point.
Time taken: 18.8937
Function value obtained: 0.3824
Current minimum: 0.3813
Iteration No: 126 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 151, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 155, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21879	valid-rmse:4.23715
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391444	valid-rmse:0.435799
[20]	train-rmse:0.341649	valid-rmse:0.389637
[30]	train-rmse:0.333009	valid-rmse:0.383663
[39]	train-rmse:0.329841	valid-rmse:0.382402
Iteration No: 126 ended. Search finished for the next optimal point.
Time taken: 19.5547
Function value obtained: 0.3824
Current minimum: 0.3813
Iteration No: 127 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.18418800201069097, 'colsample_bytree': 0.40000000000000002, 'max_depth': 81, 'subsample': 1.0, 'lambda': 38.186247854002026, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90461	valid-rmse:4.92272
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.762746	valid-rmse:0.794188
[20]	train-rmse:0.372167	valid-rmse:0.418083
[30]	train-rmse:0.341431	valid-rmse:0.389557
[39]	train-rmse:0.333669	valid-rmse:0.383601
Iteration No: 127 ended. Search finished for the next optimal point.
Time taken: 7.4662
Function value obtained: 0.3836
Current minimum: 0.3813
Iteration No: 128 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 13, 'eta': 0.16438989669859622, 'colsample_bytree': 0.98162593443777513, 'max_depth': 196, 'subsample': 0.98643754869191547, 'lambda': 81.060772217724463, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02322	valid-rmse:5.04134
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.933692	valid-rmse:0.962298
[20]	train-rmse:0.39223	valid-rmse:0.438861
[30]	train-rmse:0.34062	valid-rmse:0.392542
[39]	train-rmse:0.329785	valid-rmse:0.384865
Iteration No: 128 ended. Search finished for the next optimal point.
Time taken: 17.1617
Function value obtained: 0.3849
Current minimum: 0.3813
Iteration No: 129 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 281, 'eta': 0.2419794586924712, 'colsample_bytree': 0.68956925417841952, 'max_depth': 8, 'subsample': 0.93077180728794273, 'lambda': 0.96242993160440538, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55751	valid-rmse:4.57523
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.467301	valid-rmse:0.507116
[20]	train-rmse:0.354315	valid-rmse:0.399068
[30]	train-rmse:0.348441	valid-rmse:0.3936
[39]	train-rmse:0.345613	valid-rmse:0.391195
Iteration No: 129 ended. Search finished for the next optimal point.
Time taken: 5.6730
Function value obtained: 0.3912
Current minimum: 0.3813
Iteration No: 130 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.19846963992865554, 'colsample_bytree': 1.0, 'max_depth': 114, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.82106	valid-rmse:4.83921
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.667732	valid-rmse:0.702309
[20]	train-rmse:0.357153	valid-rmse:0.407027
[30]	train-rmse:0.33255	valid-rmse:0.387019
[39]	train-rmse:0.325516	valid-rmse:0.383182
Iteration No: 130 ended. Search finished for the next optimal point.
Time taken: 20.6388
Function value obtained: 0.3832
Current minimum: 0.3813
Iteration No: 131 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.24254985626609918, 'colsample_bytree': 1.0, 'max_depth': 153, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55253	valid-rmse:4.56996
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.452852	valid-rmse:0.494202
[20]	train-rmse:0.340388	valid-rmse:0.387989
[30]	train-rmse:0.334681	valid-rmse:0.383701
[39]	train-rmse:0.332363	valid-rmse:0.382493
Iteration No: 131 ended. Search finished for the next optimal point.
Time taken: 22.2864
Function value obtained: 0.3825
Current minimum: 0.3813
Iteration No: 132 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 164, 'eta': 0.29999999999999999, 'colsample_bytree': 0.40000000000000002, 'max_depth': 159, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21907	valid-rmse:4.23748
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.40185	valid-rmse:0.445806
[20]	train-rmse:0.347646	valid-rmse:0.394463
[30]	train-rmse:0.336325	valid-rmse:0.385574
[39]	train-rmse:0.331545	valid-rmse:0.382423
Iteration No: 132 ended. Search finished for the next optimal point.
Time taken: 8.5373
Function value obtained: 0.3824
Current minimum: 0.3813
Iteration No: 133 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 145, 'eta': 0.23926193117280325, 'colsample_bytree': 1.0, 'max_depth': 147, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.57896	valid-rmse:4.59718
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.492816	valid-rmse:0.532662
[20]	train-rmse:0.347946	valid-rmse:0.394921
[30]	train-rmse:0.335761	valid-rmse:0.38468
[39]	train-rmse:0.330908	valid-rmse:0.3815
Iteration No: 133 ended. Search finished for the next optimal point.
Time taken: 16.3549
Function value obtained: 0.3815
Current minimum: 0.3813
Iteration No: 134 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 261, 'eta': 0.17758921638192732, 'colsample_bytree': 0.88151839971795609, 'max_depth': 43, 'subsample': 0.9931479836478122, 'lambda': 87.243146850061677, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94524	valid-rmse:4.96347
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.816308	valid-rmse:0.846961
[20]	train-rmse:0.379379	valid-rmse:0.424611
[30]	train-rmse:0.345483	valid-rmse:0.392096
[39]	train-rmse:0.338096	valid-rmse:0.385496
Iteration No: 134 ended. Search finished for the next optimal point.
Time taken: 11.3674
Function value obtained: 0.3855
Current minimum: 0.3813
Iteration No: 135 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 206, 'eta': 0.17707891038229731, 'colsample_bytree': 1.0, 'max_depth': 76, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94319	valid-rmse:4.96075
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.788821	valid-rmse:0.818708
[20]	train-rmse:0.356742	valid-rmse:0.404858
[30]	train-rmse:0.335467	valid-rmse:0.385231
[39]	train-rmse:0.33175	valid-rmse:0.382647
Iteration No: 135 ended. Search finished for the next optimal point.
Time taken: 20.2976
Function value obtained: 0.3826
Current minimum: 0.3813
Iteration No: 136 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 298, 'eta': 0.29959406010740686, 'colsample_bytree': 0.98252231369800047, 'max_depth': 111, 'subsample': 0.92428804862647052, 'lambda': 87.786088657493437, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2214	valid-rmse:4.23977
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395759	valid-rmse:0.439378
[20]	train-rmse:0.345531	valid-rmse:0.391204
[30]	train-rmse:0.337288	valid-rmse:0.384767
[39]	train-rmse:0.333666	valid-rmse:0.382433
Iteration No: 136 ended. Search finished for the next optimal point.
Time taken: 16.0282
Function value obtained: 0.3824
Current minimum: 0.3813
Iteration No: 137 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 295, 'eta': 0.24840173867628473, 'colsample_bytree': 0.88133611126330691, 'max_depth': 119, 'subsample': 0.96918148960660111, 'lambda': 87.684056391754112, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.52516	valid-rmse:4.54352
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.472264	valid-rmse:0.512824
[20]	train-rmse:0.35078	valid-rmse:0.396294
[30]	train-rmse:0.33955	valid-rmse:0.386461
[39]	train-rmse:0.334664	valid-rmse:0.382725
Iteration No: 137 ended. Search finished for the next optimal point.
Time taken: 13.1073
Function value obtained: 0.3827
Current minimum: 0.3813
Iteration No: 138 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 172, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 154, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2188	valid-rmse:4.23716
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391749	valid-rmse:0.43626
[20]	train-rmse:0.341689	valid-rmse:0.389127
[30]	train-rmse:0.333629	valid-rmse:0.383277
[39]	train-rmse:0.329962	valid-rmse:0.381307
Iteration No: 138 ended. Search finished for the next optimal point.
Time taken: 19.0600
Function value obtained: 0.3813
Current minimum: 0.3813
Iteration No: 139 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 41, 'eta': 0.16871944995199184, 'colsample_bytree': 0.98478620171367925, 'max_depth': 6, 'subsample': 0.95060449096566657, 'lambda': 0.22404064143325242, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99374	valid-rmse:5.01138
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.876654	valid-rmse:0.904721
[20]	train-rmse:0.390798	valid-rmse:0.43467
[30]	train-rmse:0.360406	valid-rmse:0.405138
[39]	train-rmse:0.354401	valid-rmse:0.399459
Iteration No: 139 ended. Search finished for the next optimal point.
Time taken: 5.7533
Function value obtained: 0.3995
Current minimum: 0.3813
Iteration No: 140 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 115, 'eta': 0.22217783752381443, 'colsample_bytree': 0.93389010134247485, 'max_depth': 81, 'subsample': 0.80545818602201047, 'lambda': 86.531077157044422, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.68079	valid-rmse:4.69898
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.552655	valid-rmse:0.590086
[20]	train-rmse:0.352262	valid-rmse:0.399056
[30]	train-rmse:0.337721	valid-rmse:0.386563
[39]	train-rmse:0.332478	valid-rmse:0.38306
Iteration No: 140 ended. Search finished for the next optimal point.
Time taken: 14.2823
Function value obtained: 0.3831
Current minimum: 0.3813
Iteration No: 141 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.295186201563649, 'colsample_bytree': 0.69409112132796502, 'max_depth': 191, 'subsample': 0.82266456127039578, 'lambda': 89.145899320484361, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.24842	valid-rmse:4.26692
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.402398	valid-rmse:0.44565
[20]	train-rmse:0.352405	valid-rmse:0.397024
[30]	train-rmse:0.344252	valid-rmse:0.389383
[39]	train-rmse:0.341065	valid-rmse:0.386831
Iteration No: 141 ended. Search finished for the next optimal point.
Time taken: 10.4122
Function value obtained: 0.3868
Current minimum: 0.3813
Iteration No: 142 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.1930265784555843, 'colsample_bytree': 0.40000000000000002, 'max_depth': 71, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84854	valid-rmse:4.86601
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.677984	valid-rmse:0.710223
[20]	train-rmse:0.357034	valid-rmse:0.403256
[30]	train-rmse:0.340603	valid-rmse:0.387939
[39]	train-rmse:0.335916	valid-rmse:0.384405
Iteration No: 142 ended. Search finished for the next optimal point.
Time taken: 9.0706
Function value obtained: 0.3844
Current minimum: 0.3813
Iteration No: 143 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 16, 'eta': 0.14227801213710656, 'colsample_bytree': 0.44630463636801798, 'max_depth': 139, 'subsample': 0.93403319329714107, 'lambda': 1.2248520377788372, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.15181	valid-rmse:5.16967
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.17244	valid-rmse:1.19744
[20]	train-rmse:0.420681	valid-rmse:0.470212
[30]	train-rmse:0.33059	valid-rmse:0.391608
[39]	train-rmse:0.321258	valid-rmse:0.385056
Iteration No: 143 ended. Search finished for the next optimal point.
Time taken: 14.6063
Function value obtained: 0.3851
Current minimum: 0.3813
Iteration No: 144 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 223, 'eta': 0.26379376199202664, 'colsample_bytree': 0.41215075945393231, 'max_depth': 71, 'subsample': 0.99937813987637192, 'lambda': 52.404636376260356, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.43232	valid-rmse:4.45075
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.438335	valid-rmse:0.480618
[20]	train-rmse:0.347443	valid-rmse:0.394026
[30]	train-rmse:0.33619	valid-rmse:0.384876
[39]	train-rmse:0.331929	valid-rmse:0.382149
Iteration No: 144 ended. Search finished for the next optimal point.
Time taken: 8.9887
Function value obtained: 0.3821
Current minimum: 0.3813
Iteration No: 145 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 151, 'eta': 0.19341228316227677, 'colsample_bytree': 0.40000000000000002, 'max_depth': 73, 'subsample': 1.0, 'lambda': 48.7927107517107, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85015	valid-rmse:4.8683
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.700853	valid-rmse:0.733872
[20]	train-rmse:0.36715	valid-rmse:0.413214
[30]	train-rmse:0.341119	valid-rmse:0.389277
[39]	train-rmse:0.333917	valid-rmse:0.383636
Iteration No: 145 ended. Search finished for the next optimal point.
Time taken: 7.6828
Function value obtained: 0.3836
Current minimum: 0.3813
Iteration No: 146 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 143, 'eta': 0.26568721507621373, 'colsample_bytree': 1.0, 'max_depth': 124, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.42221	valid-rmse:4.44048
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.43319	valid-rmse:0.475727
[20]	train-rmse:0.343825	valid-rmse:0.390849
[30]	train-rmse:0.334417	valid-rmse:0.38355
[39]	train-rmse:0.329871	valid-rmse:0.380916
Iteration No: 146 ended. Search finished for the next optimal point.
Time taken: 18.4807
Function value obtained: 0.3809
Current minimum: 0.3809
Iteration No: 147 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 28, 'eta': 0.12089088679022261, 'colsample_bytree': 0.95670631701970144, 'max_depth': 196, 'subsample': 0.97406277067651881, 'lambda': 0.20391325808058219, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.27871	valid-rmse:5.2964
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.49761	valid-rmse:1.51959
[20]	train-rmse:0.531178	valid-rmse:0.57079
[30]	train-rmse:0.357973	valid-rmse:0.408533
[39]	train-rmse:0.338151	valid-rmse:0.389772
Iteration No: 147 ended. Search finished for the next optimal point.
Time taken: 20.5927
Function value obtained: 0.3898
Current minimum: 0.3809
Iteration No: 148 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 290, 'eta': 0.25359528045460322, 'colsample_bytree': 0.47668001687219153, 'max_depth': 198, 'subsample': 0.99475220450706647, 'lambda': 0.57244719798677612, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.48814	valid-rmse:4.50574
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.42973	valid-rmse:0.472158
[20]	train-rmse:0.339708	valid-rmse:0.386956
[30]	train-rmse:0.334017	valid-rmse:0.382584
[39]	train-rmse:0.331156	valid-rmse:0.38078
Iteration No: 148 ended. Search finished for the next optimal point.
Time taken: 12.1889
Function value obtained: 0.3808
Current minimum: 0.3808
Iteration No: 149 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 290, 'eta': 0.15365655370294592, 'colsample_bytree': 0.62483879866288605, 'max_depth': 95, 'subsample': 0.97699836795153883, 'lambda': 0.29652225150180789, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.08357	valid-rmse:5.10126
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.02615	valid-rmse:1.05178
[20]	train-rmse:0.395931	valid-rmse:0.440372
[30]	train-rmse:0.345521	valid-rmse:0.392262
[39]	train-rmse:0.340101	valid-rmse:0.387063
Iteration No: 149 ended. Search finished for the next optimal point.
Time taken: 10.6859
Function value obtained: 0.3871
Current minimum: 0.3808
Iteration No: 150 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26610375146616527, 'colsample_bytree': 1.0, 'max_depth': 136, 'subsample': 1.0, 'lambda': 39.21548820455665, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4176	valid-rmse:4.43595
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.426319	valid-rmse:0.469267
[20]	train-rmse:0.343696	valid-rmse:0.390339
[30]	train-rmse:0.33581	valid-rmse:0.384232
[39]	train-rmse:0.332324	valid-rmse:0.382179
Iteration No: 150 ended. Search finished for the next optimal point.
Time taken: 17.9599
Function value obtained: 0.3822
Current minimum: 0.3808
Iteration No: 151 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 11, 'eta': 0.25724454977254241, 'colsample_bytree': 0.51536533198965084, 'max_depth': 49, 'subsample': 0.96540539084494392, 'lambda': 80.491675590417614, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.47248	valid-rmse:4.49088
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.44995	valid-rmse:0.492613
[20]	train-rmse:0.340576	valid-rmse:0.391765
[30]	train-rmse:0.328037	valid-rmse:0.383798
[39]	train-rmse:0.323096	valid-rmse:0.382026
Iteration No: 151 ended. Search finished for the next optimal point.
Time taken: 13.7199
Function value obtained: 0.3820
Current minimum: 0.3808
Iteration No: 152 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 17, 'eta': 0.24024979483509887, 'colsample_bytree': 0.41065300181224468, 'max_depth': 66, 'subsample': 0.84859350514100396, 'lambda': 87.03163262259794, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.57378	valid-rmse:4.59215
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.496797	valid-rmse:0.537387
[20]	train-rmse:0.349577	valid-rmse:0.399134
[30]	train-rmse:0.333455	valid-rmse:0.386656
[39]	train-rmse:0.327161	valid-rmse:0.382987
Iteration No: 152 ended. Search finished for the next optimal point.
Time taken: 10.7002
Function value obtained: 0.3830
Current minimum: 0.3808
Iteration No: 153 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 28, 'eta': 0.29715332074459833, 'colsample_bytree': 0.8917988391878402, 'max_depth': 6, 'subsample': 0.89450338597507373, 'lambda': 88.611847531246568, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.23641	valid-rmse:4.25488
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.406765	valid-rmse:0.449882
[20]	train-rmse:0.362882	valid-rmse:0.407099
[30]	train-rmse:0.355282	valid-rmse:0.40041
[39]	train-rmse:0.350178	valid-rmse:0.395949
Iteration No: 153 ended. Search finished for the next optimal point.
Time taken: 5.8208
Function value obtained: 0.3959
Current minimum: 0.3808
Iteration No: 154 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.21284584707622173, 'colsample_bytree': 0.40000000000000002, 'max_depth': 81, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.73588	valid-rmse:4.75411
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.599913	valid-rmse:0.636498
[20]	train-rmse:0.359952	valid-rmse:0.408839
[30]	train-rmse:0.336492	valid-rmse:0.390012
[39]	train-rmse:0.327979	valid-rmse:0.384706
Iteration No: 154 ended. Search finished for the next optimal point.
Time taken: 10.4262
Function value obtained: 0.3847
Current minimum: 0.3808
Iteration No: 155 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 295, 'eta': 0.16162108001098974, 'colsample_bytree': 0.94554964669824249, 'max_depth': 83, 'subsample': 0.95542541374538492, 'lambda': 78.045001529140379, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.03967	valid-rmse:5.0578
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.964137	valid-rmse:0.992001
[20]	train-rmse:0.40274	valid-rmse:0.446829
[30]	train-rmse:0.350855	valid-rmse:0.397259
[39]	train-rmse:0.341067	valid-rmse:0.387957
Iteration No: 155 ended. Search finished for the next optimal point.
Time taken: 11.1792
Function value obtained: 0.3880
Current minimum: 0.3808
Iteration No: 156 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 119, 'eta': 0.26435752864449125, 'colsample_bytree': 1.0, 'max_depth': 114, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4301	valid-rmse:4.44837
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.435727	valid-rmse:0.478877
[20]	train-rmse:0.343509	valid-rmse:0.391657
[30]	train-rmse:0.33284	valid-rmse:0.383384
[39]	train-rmse:0.328918	valid-rmse:0.381445
Iteration No: 156 ended. Search finished for the next optimal point.
Time taken: 18.6616
Function value obtained: 0.3814
Current minimum: 0.3808
Iteration No: 157 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 15, 'eta': 0.26501061572530538, 'colsample_bytree': 0.50699890636656786, 'max_depth': 195, 'subsample': 0.99125875741466762, 'lambda': 88.345986830106057, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.42656	valid-rmse:4.4449
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.436637	valid-rmse:0.479976
[20]	train-rmse:0.340445	valid-rmse:0.39182
[30]	train-rmse:0.328556	valid-rmse:0.384019
[39]	train-rmse:0.323707	valid-rmse:0.38228
Iteration No: 157 ended. Search finished for the next optimal point.
Time taken: 14.3004
Function value obtained: 0.3823
Current minimum: 0.3808
Iteration No: 158 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.29985729466788014, 'colsample_bytree': 0.60616685696836403, 'max_depth': 200, 'subsample': 0.88978943494637142, 'lambda': 84.281361131971408, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22023	valid-rmse:4.23875
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.393481	valid-rmse:0.439701
[20]	train-rmse:0.337474	valid-rmse:0.390412
[30]	train-rmse:0.327464	valid-rmse:0.38535
[39]	train-rmse:0.3237	valid-rmse:0.384342
Iteration No: 158 ended. Search finished for the next optimal point.
Time taken: 18.0105
Function value obtained: 0.3843
Current minimum: 0.3808
Iteration No: 159 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 126, 'eta': 0.26790085734611391, 'colsample_bytree': 0.40000000000000002, 'max_depth': 122, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.40934	valid-rmse:4.42767
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.438068	valid-rmse:0.480908
[20]	train-rmse:0.349701	valid-rmse:0.397346
[30]	train-rmse:0.336617	valid-rmse:0.38686
[39]	train-rmse:0.33132	valid-rmse:0.383388
Iteration No: 159 ended. Search finished for the next optimal point.
Time taken: 8.9878
Function value obtained: 0.3834
Current minimum: 0.3808
Iteration No: 160 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 170, 'eta': 0.18930275376491143, 'colsample_bytree': 1.0, 'max_depth': 77, 'subsample': 1.0, 'lambda': 42.813981497114604, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87409	valid-rmse:4.89229
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.71984	valid-rmse:0.751993
[20]	train-rmse:0.36161	valid-rmse:0.407798
[30]	train-rmse:0.337529	valid-rmse:0.385638
[39]	train-rmse:0.331829	valid-rmse:0.381688
Iteration No: 160 ended. Search finished for the next optimal point.
Time taken: 15.6254
Function value obtained: 0.3817
Current minimum: 0.3808
Iteration No: 161 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.22186328410879541, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.67592	valid-rmse:4.69339
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.520313	valid-rmse:0.558556
[20]	train-rmse:0.342122	valid-rmse:0.390011
[30]	train-rmse:0.334683	valid-rmse:0.383654
[39]	train-rmse:0.332475	valid-rmse:0.382467
Iteration No: 161 ended. Search finished for the next optimal point.
Time taken: 20.9168
Function value obtained: 0.3825
Current minimum: 0.3808
Iteration No: 162 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 152, 'subsample': 1.0, 'lambda': 46.022138427657552, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21666	valid-rmse:4.23511
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.388361	valid-rmse:0.432562
[20]	train-rmse:0.342348	valid-rmse:0.388787
[30]	train-rmse:0.335282	valid-rmse:0.383506
[39]	train-rmse:0.332557	valid-rmse:0.382122
Iteration No: 162 ended. Search finished for the next optimal point.
Time taken: 18.9903
Function value obtained: 0.3821
Current minimum: 0.3808
Iteration No: 163 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.26219944903809322, 'colsample_bytree': 1.0, 'max_depth': 114, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4429	valid-rmse:4.46116
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.437525	valid-rmse:0.481486
[20]	train-rmse:0.338472	valid-rmse:0.391663
[30]	train-rmse:0.327339	valid-rmse:0.385233
[39]	train-rmse:0.32295	valid-rmse:0.384003
Iteration No: 163 ended. Search finished for the next optimal point.
Time taken: 27.1892
Function value obtained: 0.3840
Current minimum: 0.3808
Iteration No: 164 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 23, 'eta': 0.17971408815179241, 'colsample_bytree': 0.95354288431350342, 'max_depth': 196, 'subsample': 0.97590993489532663, 'lambda': 8.2409356217797072, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92922	valid-rmse:4.9471
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.780197	valid-rmse:0.810981
[20]	train-rmse:0.354265	valid-rmse:0.407266
[30]	train-rmse:0.326614	valid-rmse:0.385909
[39]	train-rmse:0.321985	valid-rmse:0.384466
Iteration No: 164 ended. Search finished for the next optimal point.
Time taken: 27.9913
Function value obtained: 0.3845
Current minimum: 0.3808
Iteration No: 165 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 280, 'eta': 0.29944969555013412, 'colsample_bytree': 0.99916925422864422, 'max_depth': 86, 'subsample': 0.96877199982219631, 'lambda': 55.047936778977039, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22039	valid-rmse:4.23883
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.389639	valid-rmse:0.434111
[20]	train-rmse:0.343056	valid-rmse:0.389807
[30]	train-rmse:0.335703	valid-rmse:0.384255
[39]	train-rmse:0.332368	valid-rmse:0.382279
Iteration No: 165 ended. Search finished for the next optimal point.
Time taken: 18.9701
Function value obtained: 0.3823
Current minimum: 0.3808
Iteration No: 166 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 291, 'eta': 0.24178162455317634, 'colsample_bytree': 0.96303844058270127, 'max_depth': 71, 'subsample': 0.82575510918430206, 'lambda': 32.117797323621971, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.56201	valid-rmse:4.58028
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.478295	valid-rmse:0.518301
[20]	train-rmse:0.34806	valid-rmse:0.394412
[30]	train-rmse:0.337985	valid-rmse:0.385368
[39]	train-rmse:0.334207	valid-rmse:0.38273
Iteration No: 166 ended. Search finished for the next optimal point.
Time taken: 15.5853
Function value obtained: 0.3827
Current minimum: 0.3808
Iteration No: 167 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26610007647044476, 'colsample_bytree': 1.0, 'max_depth': 123, 'subsample': 1.0, 'lambda': 39.014538397249588, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41761	valid-rmse:4.43596
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.42631	valid-rmse:0.469264
[20]	train-rmse:0.343919	valid-rmse:0.390502
[30]	train-rmse:0.336101	valid-rmse:0.384478
[39]	train-rmse:0.332405	valid-rmse:0.382221
Iteration No: 167 ended. Search finished for the next optimal point.
Time taken: 17.7270
Function value obtained: 0.3822
Current minimum: 0.3808
Iteration No: 168 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.19350684585004818, 'colsample_bytree': 0.40000000000000002, 'max_depth': 70, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84568	valid-rmse:4.86315
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.675168	valid-rmse:0.707387
[20]	train-rmse:0.357208	valid-rmse:0.403138
[30]	train-rmse:0.34098	valid-rmse:0.388065
[39]	train-rmse:0.336313	valid-rmse:0.384634
Iteration No: 168 ended. Search finished for the next optimal point.
Time taken: 9.4920
Function value obtained: 0.3846
Current minimum: 0.3808
Iteration No: 169 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 12, 'eta': 0.12928341048938011, 'colsample_bytree': 0.95244359028660819, 'max_depth': 73, 'subsample': 0.95276875102925163, 'lambda': 88.029059056111194, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.23198	valid-rmse:5.25007
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.38193	valid-rmse:1.40614
[20]	train-rmse:0.510801	valid-rmse:0.551091
[30]	train-rmse:0.365755	valid-rmse:0.414685
[39]	train-rmse:0.340695	valid-rmse:0.392486
Iteration No: 169 ended. Search finished for the next optimal point.
Time taken: 14.3100
Function value obtained: 0.3925
Current minimum: 0.3808
Iteration No: 170 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 12, 'eta': 0.29914990914584794, 'colsample_bytree': 0.60779342661734903, 'max_depth': 198, 'subsample': 0.98183580320996988, 'lambda': 24.288017919565366, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22057	valid-rmse:4.23869
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.380848	valid-rmse:0.429609
[20]	train-rmse:0.331008	valid-rmse:0.390429
[30]	train-rmse:0.324549	valid-rmse:0.388913
[39]	train-rmse:0.322782	valid-rmse:0.389198
Iteration No: 170 ended. Search finished for the next optimal point.
Time taken: 24.2872
Function value obtained: 0.3892
Current minimum: 0.3808
Iteration No: 171 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 29, 'eta': 0.2999985254171128, 'colsample_bytree': 0.42973518448756087, 'max_depth': 61, 'subsample': 0.99139317930601023, 'lambda': 85.8603439041527, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21909	valid-rmse:4.23752
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.398056	valid-rmse:0.44246
[20]	train-rmse:0.349163	valid-rmse:0.395441
[30]	train-rmse:0.340733	valid-rmse:0.388029
[39]	train-rmse:0.33799	valid-rmse:0.385868
Iteration No: 171 ended. Search finished for the next optimal point.
Time taken: 11.2859
Function value obtained: 0.3859
Current minimum: 0.3808
Iteration No: 172 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 298, 'eta': 0.18546479561014079, 'colsample_bytree': 0.98416384430684212, 'max_depth': 105, 'subsample': 0.84513296654334713, 'lambda': 5.8287538614395649, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89494	valid-rmse:4.91283
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.736288	valid-rmse:0.767368
[20]	train-rmse:0.359861	valid-rmse:0.405741
[30]	train-rmse:0.339636	valid-rmse:0.386465
[39]	train-rmse:0.335285	valid-rmse:0.38283
Iteration No: 172 ended. Search finished for the next optimal point.
Time taken: 15.3451
Function value obtained: 0.3828
Current minimum: 0.3808
Iteration No: 173 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 26, 'eta': 0.12183928183959471, 'colsample_bytree': 0.88899022885359047, 'max_depth': 16, 'subsample': 0.8069265642627661, 'lambda': 86.487417844617369, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.27661	valid-rmse:5.29475
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.50601	valid-rmse:1.52949
[20]	train-rmse:0.559633	valid-rmse:0.597847
[30]	train-rmse:0.3786	valid-rmse:0.425712
[39]	train-rmse:0.347305	valid-rmse:0.396416
Iteration No: 173 ended. Search finished for the next optimal point.
Time taken: 10.0198
Function value obtained: 0.3964
Current minimum: 0.3808
Iteration No: 174 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 244, 'eta': 0.27917524690838091, 'colsample_bytree': 0.55478204203763948, 'max_depth': 6, 'subsample': 0.99757132141990279, 'lambda': 89.58993570089325, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.3427	valid-rmse:4.36108
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.426958	valid-rmse:0.469047
[20]	train-rmse:0.365416	valid-rmse:0.40868
[30]	train-rmse:0.356802	valid-rmse:0.400688
[39]	train-rmse:0.352611	valid-rmse:0.397094
Iteration No: 174 ended. Search finished for the next optimal point.
Time taken: 5.1442
Function value obtained: 0.3971
Current minimum: 0.3808
Iteration No: 175 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 162, 'eta': 0.18962112179608737, 'colsample_bytree': 1.0, 'max_depth': 84, 'subsample': 0.8886080888025174, 'lambda': 34.973923086005037, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87206	valid-rmse:4.89026
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.717431	valid-rmse:0.7498
[20]	train-rmse:0.361063	valid-rmse:0.407448
[30]	train-rmse:0.338325	valid-rmse:0.386535
[39]	train-rmse:0.332359	valid-rmse:0.382062
Iteration No: 175 ended. Search finished for the next optimal point.
Time taken: 15.8930
Function value obtained: 0.3821
Current minimum: 0.3808
Iteration No: 176 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 47, 'eta': 0.14761564290268983, 'colsample_bytree': 0.53382616957490225, 'max_depth': 103, 'subsample': 0.80286699069197831, 'lambda': 2.483577513693517, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.12024	valid-rmse:5.13805
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.10434	valid-rmse:1.12966
[20]	train-rmse:0.407172	valid-rmse:0.453264
[30]	train-rmse:0.334479	valid-rmse:0.387569
[39]	train-rmse:0.326214	valid-rmse:0.381527
Iteration No: 176 ended. Search finished for the next optimal point.
Time taken: 13.5078
Function value obtained: 0.3815
Current minimum: 0.3808
Iteration No: 177 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 121, 'eta': 0.26760072303234728, 'colsample_bytree': 0.75867362693782614, 'max_depth': 143, 'subsample': 0.80083211331446014, 'lambda': 86.933138248629447, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41188	valid-rmse:4.43029
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.432593	valid-rmse:0.474755
[20]	train-rmse:0.345168	valid-rmse:0.391745
[30]	train-rmse:0.33529	valid-rmse:0.383823
[39]	train-rmse:0.331676	valid-rmse:0.381886
Iteration No: 177 ended. Search finished for the next optimal point.
Time taken: 14.8046
Function value obtained: 0.3819
Current minimum: 0.3808
Iteration No: 178 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 200, 'eta': 0.17920550303331154, 'colsample_bytree': 1.0, 'max_depth': 93, 'subsample': 0.86367449597961077, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93048	valid-rmse:4.94799
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.771228	valid-rmse:0.80126
[20]	train-rmse:0.355757	valid-rmse:0.403677
[30]	train-rmse:0.335865	valid-rmse:0.385321
[39]	train-rmse:0.332194	valid-rmse:0.382552
Iteration No: 178 ended. Search finished for the next optimal point.
Time taken: 20.7653
Function value obtained: 0.3826
Current minimum: 0.3808
Iteration No: 179 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 60, 'eta': 0.1712730467661755, 'colsample_bytree': 0.79802845995723093, 'max_depth': 56, 'subsample': 0.80176227676817524, 'lambda': 67.394656423074835, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98268	valid-rmse:5.00088
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.869084	valid-rmse:0.899064
[20]	train-rmse:0.383491	valid-rmse:0.430099
[30]	train-rmse:0.342546	valid-rmse:0.39209
[39]	train-rmse:0.333973	valid-rmse:0.385039
Iteration No: 179 ended. Search finished for the next optimal point.
Time taken: 13.2062
Function value obtained: 0.3850
Current minimum: 0.3808
Iteration No: 180 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.20882060276128894, 'colsample_bytree': 1.0, 'max_depth': 124, 'subsample': 0.88508838214570951, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.75382	valid-rmse:4.77134
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.58063	valid-rmse:0.616218
[20]	train-rmse:0.345531	valid-rmse:0.392703
[30]	train-rmse:0.336495	valid-rmse:0.384723
[39]	train-rmse:0.3338	valid-rmse:0.382934
Iteration No: 180 ended. Search finished for the next optimal point.
Time taken: 18.7891
Function value obtained: 0.3829
Current minimum: 0.3808
Iteration No: 181 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.19199025226728778, 'colsample_bytree': 1.0, 'max_depth': 101, 'subsample': 0.82588865981039017, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8599	valid-rmse:4.87806
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.7103	valid-rmse:0.743401
[20]	train-rmse:0.363429	valid-rmse:0.411918
[30]	train-rmse:0.336117	valid-rmse:0.388392
[39]	train-rmse:0.328757	valid-rmse:0.384013
Iteration No: 181 ended. Search finished for the next optimal point.
Time taken: 20.2772
Function value obtained: 0.3840
Current minimum: 0.3808
Iteration No: 182 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 169, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 0.80000000000000004, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21959	valid-rmse:4.23796
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.394197	valid-rmse:0.43827
[20]	train-rmse:0.34433	valid-rmse:0.391266
[30]	train-rmse:0.336089	valid-rmse:0.384857
[39]	train-rmse:0.332675	valid-rmse:0.38317
Iteration No: 182 ended. Search finished for the next optimal point.
Time taken: 18.2332
Function value obtained: 0.3832
Current minimum: 0.3808
Iteration No: 183 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 169, 'eta': 0.18148030701753134, 'colsample_bytree': 1.0, 'max_depth': 82, 'subsample': 0.86016561926987267, 'lambda': 31.876673817055845, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92035	valid-rmse:4.93853
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.776783	valid-rmse:0.807538
[20]	train-rmse:0.367874	valid-rmse:0.41376
[30]	train-rmse:0.339781	valid-rmse:0.387727
[39]	train-rmse:0.333768	valid-rmse:0.382731
Iteration No: 183 ended. Search finished for the next optimal point.
Time taken: 15.8425
Function value obtained: 0.3827
Current minimum: 0.3808
Iteration No: 184 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 214, 'eta': 0.17272094274404279, 'colsample_bytree': 1.0, 'max_depth': 92, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96926	valid-rmse:4.98681
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.827018	valid-rmse:0.855682
[20]	train-rmse:0.361829	valid-rmse:0.40874
[30]	train-rmse:0.337153	valid-rmse:0.385657
[39]	train-rmse:0.333206	valid-rmse:0.382644
Iteration No: 184 ended. Search finished for the next optimal point.
Time taken: 18.6525
Function value obtained: 0.3826
Current minimum: 0.3808
Iteration No: 185 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 114, 'eta': 0.24299804540497222, 'colsample_bytree': 0.91229531283804632, 'max_depth': 198, 'subsample': 0.80644741867119607, 'lambda': 85.943799278208388, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55726	valid-rmse:4.57549
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.484765	valid-rmse:0.52511
[20]	train-rmse:0.34833	valid-rmse:0.394943
[30]	train-rmse:0.335976	valid-rmse:0.38438
[39]	train-rmse:0.331709	valid-rmse:0.381772
Iteration No: 185 ended. Search finished for the next optimal point.
Time taken: 15.9008
Function value obtained: 0.3818
Current minimum: 0.3808
Iteration No: 186 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 46, 'eta': 0.11481739713178946, 'colsample_bytree': 0.83831310214758958, 'max_depth': 194, 'subsample': 0.80016303122176335, 'lambda': 11.750081863523301, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.31642	valid-rmse:5.33441
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.62119	valid-rmse:1.64302
[20]	train-rmse:0.598564	valid-rmse:0.634672
[30]	train-rmse:0.376498	valid-rmse:0.424447
[39]	train-rmse:0.339562	valid-rmse:0.391161
Iteration No: 186 ended. Search finished for the next optimal point.
Time taken: 12.9561
Function value obtained: 0.3912
Current minimum: 0.3808
Iteration No: 187 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.23046108716962002, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 40.180303553156136, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.62938	valid-rmse:4.64765
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.513397	valid-rmse:0.552322
[20]	train-rmse:0.348296	valid-rmse:0.394509
[30]	train-rmse:0.33752	valid-rmse:0.385069
[39]	train-rmse:0.333693	valid-rmse:0.382433
Iteration No: 187 ended. Search finished for the next optimal point.
Time taken: 16.6289
Function value obtained: 0.3824
Current minimum: 0.3808
Iteration No: 188 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 112, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21879	valid-rmse:4.23714
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.389419	valid-rmse:0.436215
[20]	train-rmse:0.334761	valid-rmse:0.38915
[30]	train-rmse:0.326479	valid-rmse:0.385701
[39]	train-rmse:0.322858	valid-rmse:0.384953
Iteration No: 188 ended. Search finished for the next optimal point.
Time taken: 30.7379
Function value obtained: 0.3850
Current minimum: 0.3808
Iteration No: 189 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 0.40000000000000002, 'max_depth': 200, 'subsample': 1.0, 'lambda': 39.597213428776485, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2168	valid-rmse:4.23519
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.396493	valid-rmse:0.440007
[20]	train-rmse:0.347718	valid-rmse:0.393738
[30]	train-rmse:0.338104	valid-rmse:0.386064
[39]	train-rmse:0.334239	valid-rmse:0.383672
Iteration No: 189 ended. Search finished for the next optimal point.
Time taken: 9.7884
Function value obtained: 0.3837
Current minimum: 0.3808
Iteration No: 190 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 200, 'eta': 0.18290663164291054, 'colsample_bytree': 0.69240449719430996, 'max_depth': 118, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90841	valid-rmse:4.92594
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.742178	valid-rmse:0.772941
[20]	train-rmse:0.351711	valid-rmse:0.400047
[30]	train-rmse:0.333862	valid-rmse:0.383592
[39]	train-rmse:0.330315	valid-rmse:0.381177
Iteration No: 190 ended. Search finished for the next optimal point.
Time taken: 16.7000
Function value obtained: 0.3812
Current minimum: 0.3808
Iteration No: 191 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 298, 'eta': 0.2944537439628554, 'colsample_bytree': 0.94824133749091055, 'max_depth': 90, 'subsample': 0.99405161201429593, 'lambda': 1.8769550535308572, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.245	valid-rmse:4.26272
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.37579	valid-rmse:0.421771
[20]	train-rmse:0.338798	valid-rmse:0.386942
[30]	train-rmse:0.334184	valid-rmse:0.383814
[39]	train-rmse:0.332144	valid-rmse:0.383065
Iteration No: 191 ended. Search finished for the next optimal point.
Time taken: 23.1395
Function value obtained: 0.3831
Current minimum: 0.3808
Iteration No: 192 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 276, 'eta': 0.29946886527027639, 'colsample_bytree': 0.79192089437205748, 'max_depth': 72, 'subsample': 0.97663159485019024, 'lambda': 43.200854628944747, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22023	valid-rmse:4.23887
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.390698	valid-rmse:0.435253
[20]	train-rmse:0.346873	valid-rmse:0.392358
[30]	train-rmse:0.341281	valid-rmse:0.387637
[39]	train-rmse:0.338632	valid-rmse:0.385311
Iteration No: 192 ended. Search finished for the next optimal point.
Time taken: 14.7774
Function value obtained: 0.3853
Current minimum: 0.3808
Iteration No: 193 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 0.40000000000000002, 'max_depth': 122, 'subsample': 1.0, 'lambda': 39.03969972724844, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21679	valid-rmse:4.23513
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395794	valid-rmse:0.439566
[20]	train-rmse:0.34721	valid-rmse:0.393566
[30]	train-rmse:0.338042	valid-rmse:0.386358
[39]	train-rmse:0.333933	valid-rmse:0.3839
Iteration No: 193 ended. Search finished for the next optimal point.
Time taken: 9.8092
Function value obtained: 0.3839
Current minimum: 0.3808
Iteration No: 194 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 284, 'eta': 0.17054981790012999, 'colsample_bytree': 0.76127895494913012, 'max_depth': 54, 'subsample': 0.80644404006585135, 'lambda': 76.663959181285207, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98721	valid-rmse:5.00542
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.878617	valid-rmse:0.90792
[20]	train-rmse:0.390398	valid-rmse:0.434926
[30]	train-rmse:0.350117	valid-rmse:0.395983
[39]	train-rmse:0.341464	valid-rmse:0.387746
Iteration No: 194 ended. Search finished for the next optimal point.
Time taken: 10.4746
Function value obtained: 0.3877
Current minimum: 0.3808
Iteration No: 195 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 282, 'eta': 0.26056528550348856, 'colsample_bytree': 0.96716763904694159, 'max_depth': 134, 'subsample': 0.81147559348223064, 'lambda': 83.87960012718716, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.45301	valid-rmse:4.47129
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.446219	valid-rmse:0.487936
[20]	train-rmse:0.350761	valid-rmse:0.396514
[30]	train-rmse:0.339491	valid-rmse:0.386241
[39]	train-rmse:0.335377	valid-rmse:0.383123
Iteration No: 195 ended. Search finished for the next optimal point.
Time taken: 15.1320
Function value obtained: 0.3831
Current minimum: 0.3808
Iteration No: 196 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 20, 'eta': 0.24336122987053491, 'colsample_bytree': 0.47905883561080054, 'max_depth': 72, 'subsample': 0.99991082920309937, 'lambda': 12.320571407887391, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55123	valid-rmse:4.56916
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.464066	valid-rmse:0.506498
[20]	train-rmse:0.331928	valid-rmse:0.388353
[30]	train-rmse:0.323267	valid-rmse:0.384772
[39]	train-rmse:0.320985	valid-rmse:0.385094
Iteration No: 196 ended. Search finished for the next optimal point.
Time taken: 18.6286
Function value obtained: 0.3851
Current minimum: 0.3808
Iteration No: 197 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 195, 'eta': 0.18659806835413828, 'colsample_bytree': 0.67844407412647834, 'max_depth': 101, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8864	valid-rmse:4.90392
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.713902	valid-rmse:0.745219
[20]	train-rmse:0.34949	valid-rmse:0.397516
[30]	train-rmse:0.333213	valid-rmse:0.382805
[39]	train-rmse:0.329796	valid-rmse:0.380825
Iteration No: 197 ended. Search finished for the next optimal point.
Time taken: 16.4251
Function value obtained: 0.3808
Current minimum: 0.3808
Iteration No: 198 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 166, 'eta': 0.19298081093118419, 'colsample_bytree': 0.70993205634532908, 'max_depth': 94, 'subsample': 1.0, 'lambda': 24.038225613781645, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85166	valid-rmse:4.8696
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.691671	valid-rmse:0.724132
[20]	train-rmse:0.356472	valid-rmse:0.403144
[30]	train-rmse:0.335985	valid-rmse:0.38454
[39]	train-rmse:0.330381	valid-rmse:0.380659
Iteration No: 198 ended. Search finished for the next optimal point.
Time taken: 13.5216
Function value obtained: 0.3807
Current minimum: 0.3807
Iteration No: 199 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 14, 'eta': 0.1904547072366955, 'colsample_bytree': 0.4172088599881143, 'max_depth': 21, 'subsample': 0.91068705999650412, 'lambda': 15.756911756309199, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86627	valid-rmse:4.88427
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.709916	valid-rmse:0.742854
[20]	train-rmse:0.361182	valid-rmse:0.409225
[30]	train-rmse:0.340405	valid-rmse:0.389768
[39]	train-rmse:0.336942	valid-rmse:0.386866
Iteration No: 199 ended. Search finished for the next optimal point.
Time taken: 10.1088
Function value obtained: 0.3869
Current minimum: 0.3807
Iteration No: 200 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 15, 'eta': 0.1752921949100735, 'colsample_bytree': 0.40667948288172318, 'max_depth': 18, 'subsample': 0.96834406335393142, 'lambda': 13.789760074817577, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95633	valid-rmse:4.97431
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.825295	valid-rmse:0.855555
[20]	train-rmse:0.367812	valid-rmse:0.417489
[30]	train-rmse:0.331562	valid-rmse:0.387051
[39]	train-rmse:0.325986	valid-rmse:0.383359
Iteration No: 200 ended. Search finished for the next optimal point.
Time taken: 9.5609
Function value obtained: 0.3834
Current minimum: 0.3807
Iteration No: 201 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 15, 'eta': 0.13050460890044474, 'colsample_bytree': 0.40347546803645468, 'max_depth': 21, 'subsample': 0.87716599920352334, 'lambda': 66.89245320111776, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.22466	valid-rmse:5.24282
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.36559	valid-rmse:1.38977
[20]	train-rmse:0.509614	valid-rmse:0.549245
[30]	train-rmse:0.369419	valid-rmse:0.41689
[39]	train-rmse:0.344301	valid-rmse:0.394425
Iteration No: 201 ended. Search finished for the next optimal point.
Time taken: 8.1481
Function value obtained: 0.3944
Current minimum: 0.3807
Iteration No: 202 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 184, 'eta': 0.18560209144846218, 'colsample_bytree': 0.65325930858561931, 'max_depth': 92, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89233	valid-rmse:4.90984
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.720632	valid-rmse:0.752134
[20]	train-rmse:0.349191	valid-rmse:0.397642
[30]	train-rmse:0.332638	valid-rmse:0.382531
[39]	train-rmse:0.32917	valid-rmse:0.380228
Iteration No: 202 ended. Search finished for the next optimal point.
Time taken: 16.5703
Function value obtained: 0.3802
Current minimum: 0.3802
Iteration No: 203 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 0.72830955796510044, 'max_depth': 149, 'subsample': 1.0, 'lambda': 41.838630530098946, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21677	valid-rmse:4.23515
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.389178	valid-rmse:0.433547
[20]	train-rmse:0.342441	valid-rmse:0.389332
[30]	train-rmse:0.33521	valid-rmse:0.384096
[39]	train-rmse:0.332468	valid-rmse:0.382636
Iteration No: 203 ended. Search finished for the next optimal point.
Time taken: 15.7851
Function value obtained: 0.3826
Current minimum: 0.3802
Iteration No: 204 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 150, 'eta': 0.19286749685913307, 'colsample_bytree': 0.69949801675840639, 'max_depth': 87, 'subsample': 1.0, 'lambda': 28.044939966238676, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85249	valid-rmse:4.87038
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.693574	valid-rmse:0.726186
[20]	train-rmse:0.35713	valid-rmse:0.403977
[30]	train-rmse:0.336031	valid-rmse:0.384957
[39]	train-rmse:0.330415	valid-rmse:0.381071
Iteration No: 204 ended. Search finished for the next optimal point.
Time taken: 13.9777
Function value obtained: 0.3811
Current minimum: 0.3802
Iteration No: 205 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.20477597649920087, 'colsample_bytree': 0.75056174048054447, 'max_depth': 114, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.78195	valid-rmse:4.79934
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.603377	valid-rmse:0.638017
[20]	train-rmse:0.35003	valid-rmse:0.396945
[30]	train-rmse:0.339952	valid-rmse:0.387936
[39]	train-rmse:0.336419	valid-rmse:0.385525
Iteration No: 205 ended. Search finished for the next optimal point.
Time taken: 16.7965
Function value obtained: 0.3855
Current minimum: 0.3802
Iteration No: 206 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 29, 'eta': 0.14737294495149522, 'colsample_bytree': 0.9855365506867193, 'max_depth': 199, 'subsample': 0.84449283821536969, 'lambda': 79.449351067134444, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.12451	valid-rmse:5.14261
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.12627	valid-rmse:1.15243
[20]	train-rmse:0.433015	valid-rmse:0.476719
[30]	train-rmse:0.350071	valid-rmse:0.399191
[39]	train-rmse:0.335683	valid-rmse:0.386819
Iteration No: 206 ended. Search finished for the next optimal point.
Time taken: 15.0584
Function value obtained: 0.3868
Current minimum: 0.3802
Iteration No: 207 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 113, 'eta': 0.18045166256439032, 'colsample_bytree': 0.40000000000000002, 'max_depth': 65, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92342	valid-rmse:4.94096
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.763648	valid-rmse:0.794322
[20]	train-rmse:0.354664	valid-rmse:0.404185
[30]	train-rmse:0.333261	valid-rmse:0.385136
[39]	train-rmse:0.328678	valid-rmse:0.38235
Iteration No: 207 ended. Search finished for the next optimal point.
Time taken: 12.4399
Function value obtained: 0.3824
Current minimum: 0.3802
Iteration No: 208 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 260, 'eta': 0.19526590156767298, 'colsample_bytree': 0.93788332667983987, 'max_depth': 199, 'subsample': 0.87283124024256797, 'lambda': 88.049307940449353, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84027	valid-rmse:4.85844
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.690294	valid-rmse:0.723497
[20]	train-rmse:0.367037	valid-rmse:0.41261
[30]	train-rmse:0.344195	valid-rmse:0.390464
[39]	train-rmse:0.337433	valid-rmse:0.384714
Iteration No: 208 ended. Search finished for the next optimal point.
Time taken: 13.4813
Function value obtained: 0.3847
Current minimum: 0.3802
Iteration No: 209 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 130, 'eta': 0.18892363070798579, 'colsample_bytree': 0.6830931037379453, 'max_depth': 83, 'subsample': 1.0, 'lambda': 31.248657891791485, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87606	valid-rmse:4.89394
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.721221	valid-rmse:0.753193
[20]	train-rmse:0.359792	valid-rmse:0.406961
[30]	train-rmse:0.336337	valid-rmse:0.385756
[39]	train-rmse:0.329981	valid-rmse:0.381109
Iteration No: 209 ended. Search finished for the next optimal point.
Time taken: 13.4761
Function value obtained: 0.3811
Current minimum: 0.3802
Iteration No: 210 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 136, 'eta': 0.29999999999999999, 'colsample_bytree': 0.68293498212582815, 'max_depth': 144, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21908	valid-rmse:4.23747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.393825	valid-rmse:0.438594
[20]	train-rmse:0.341949	valid-rmse:0.390323
[30]	train-rmse:0.33262	valid-rmse:0.383328
[39]	train-rmse:0.329055	valid-rmse:0.381705
Iteration No: 210 ended. Search finished for the next optimal point.
Time taken: 16.0626
Function value obtained: 0.3817
Current minimum: 0.3802
Iteration No: 211 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 290, 'eta': 0.29168860621890702, 'colsample_bytree': 0.41538204206127621, 'max_depth': 197, 'subsample': 0.88324582246841143, 'lambda': 3.800616899641807, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.26264	valid-rmse:4.28035
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.388476	valid-rmse:0.432286
[20]	train-rmse:0.344819	valid-rmse:0.390724
[30]	train-rmse:0.338475	valid-rmse:0.385773
[39]	train-rmse:0.335914	valid-rmse:0.38402
Iteration No: 211 ended. Search finished for the next optimal point.
Time taken: 11.5285
Function value obtained: 0.3840
Current minimum: 0.3802
Iteration No: 212 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 155, 'eta': 0.1801776362977513, 'colsample_bytree': 0.56390550081796054, 'max_depth': 81, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92484	valid-rmse:4.94233
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.762059	valid-rmse:0.792353
[20]	train-rmse:0.351324	valid-rmse:0.400215
[30]	train-rmse:0.332051	valid-rmse:0.382695
[39]	train-rmse:0.328639	valid-rmse:0.380626
Iteration No: 212 ended. Search finished for the next optimal point.
Time taken: 15.9941
Function value obtained: 0.3806
Current minimum: 0.3802
Iteration No: 213 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 113, 'eta': 0.26770959766515939, 'colsample_bytree': 0.72439223578034218, 'max_depth': 128, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41059	valid-rmse:4.42887
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.431506	valid-rmse:0.474367
[20]	train-rmse:0.344217	valid-rmse:0.3922
[30]	train-rmse:0.333077	valid-rmse:0.383798
[39]	train-rmse:0.328891	valid-rmse:0.381632
Iteration No: 213 ended. Search finished for the next optimal point.
Time taken: 15.4591
Function value obtained: 0.3816
Current minimum: 0.3802
Iteration No: 214 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 284, 'eta': 0.14734661282174411, 'colsample_bytree': 0.9714192839280068, 'max_depth': 200, 'subsample': 0.96788878320952654, 'lambda': 27.566712596155831, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.12312	valid-rmse:5.1411
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.11863	valid-rmse:1.14427
[20]	train-rmse:0.425971	valid-rmse:0.468659
[30]	train-rmse:0.350655	valid-rmse:0.396968
[39]	train-rmse:0.339498	valid-rmse:0.386567
Iteration No: 214 ended. Search finished for the next optimal point.
Time taken: 13.5950
Function value obtained: 0.3866
Current minimum: 0.3802
Iteration No: 215 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 33, 'eta': 0.19428835025410501, 'colsample_bytree': 0.40116610184080559, 'max_depth': 37, 'subsample': 0.8093572519927027, 'lambda': 1.7560390479566748, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8424	valid-rmse:4.86024
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.672194	valid-rmse:0.705529
[20]	train-rmse:0.347232	valid-rmse:0.400145
[30]	train-rmse:0.330577	valid-rmse:0.38747
[39]	train-rmse:0.327596	valid-rmse:0.386519
Iteration No: 215 ended. Search finished for the next optimal point.
Time taken: 13.1627
Function value obtained: 0.3865
Current minimum: 0.3802
Iteration No: 216 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 161, 'eta': 0.17827158014770675, 'colsample_bytree': 0.7638100000551582, 'max_depth': 136, 'subsample': 1.0, 'lambda': 22.918034573224457, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93911	valid-rmse:4.95704
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.799527	valid-rmse:0.829703
[20]	train-rmse:0.367501	valid-rmse:0.413601
[30]	train-rmse:0.337705	valid-rmse:0.386242
[39]	train-rmse:0.331471	valid-rmse:0.381609
Iteration No: 216 ended. Search finished for the next optimal point.
Time taken: 14.3097
Function value obtained: 0.3816
Current minimum: 0.3802
Iteration No: 217 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 181, 'eta': 0.21593649295804146, 'colsample_bytree': 0.81595709022259588, 'max_depth': 110, 'subsample': 1.0, 'lambda': 52.475486428364924, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.71611	valid-rmse:4.73435
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.57225	valid-rmse:0.608661
[20]	train-rmse:0.351877	valid-rmse:0.398593
[30]	train-rmse:0.336189	valid-rmse:0.384598
[39]	train-rmse:0.330986	valid-rmse:0.381073
Iteration No: 217 ended. Search finished for the next optimal point.
Time taken: 15.8749
Function value obtained: 0.3811
Current minimum: 0.3802
Iteration No: 218 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 299, 'eta': 0.25243951009667265, 'colsample_bytree': 0.49358830433536388, 'max_depth': 61, 'subsample': 0.95292621141662537, 'lambda': 0.58633201487674991, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.49506	valid-rmse:4.51269
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.433012	valid-rmse:0.475394
[20]	train-rmse:0.340142	valid-rmse:0.387293
[30]	train-rmse:0.334538	valid-rmse:0.383026
[39]	train-rmse:0.331679	valid-rmse:0.381248
Iteration No: 218 ended. Search finished for the next optimal point.
Time taken: 14.1933
Function value obtained: 0.3812
Current minimum: 0.3802
Iteration No: 219 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 289, 'eta': 0.2973700033596911, 'colsample_bytree': 0.46417186419755618, 'max_depth': 21, 'subsample': 0.83850016248972259, 'lambda': 3.0890390819333082, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2287	valid-rmse:4.24646
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.381903	valid-rmse:0.426304
[20]	train-rmse:0.343678	valid-rmse:0.389645
[30]	train-rmse:0.338378	valid-rmse:0.385369
[39]	train-rmse:0.336699	valid-rmse:0.384361
Iteration No: 219 ended. Search finished for the next optimal point.
Time taken: 10.2601
Function value obtained: 0.3844
Current minimum: 0.3802
Iteration No: 220 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 50, 'eta': 0.10007196644510222, 'colsample_bytree': 0.44656957345514348, 'max_depth': 197, 'subsample': 0.82876469909536199, 'lambda': 4.2471810888214128, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.40381	valid-rmse:5.42171
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.92359	valid-rmse:1.944
[20]	train-rmse:0.758499	valid-rmse:0.789723
[30]	train-rmse:0.425218	valid-rmse:0.469235
[39]	train-rmse:0.358796	valid-rmse:0.406719
Iteration No: 220 ended. Search finished for the next optimal point.
Time taken: 10.2843
Function value obtained: 0.4067
Current minimum: 0.3802
Iteration No: 221 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 292, 'eta': 0.29736467829574431, 'colsample_bytree': 0.52074027433460457, 'max_depth': 90, 'subsample': 0.8338305296234555, 'lambda': 5.0896494342370264, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22909	valid-rmse:4.24697
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.381024	valid-rmse:0.425552
[20]	train-rmse:0.341784	valid-rmse:0.388857
[30]	train-rmse:0.335652	valid-rmse:0.384057
[39]	train-rmse:0.332998	valid-rmse:0.382618
Iteration No: 221 ended. Search finished for the next optimal point.
Time taken: 13.3854
Function value obtained: 0.3826
Current minimum: 0.3802
Iteration No: 222 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 122, 'eta': 0.29848358519058826, 'colsample_bytree': 0.40907804097796624, 'max_depth': 85, 'subsample': 0.82829763039488769, 'lambda': 49.724794512482333, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22683	valid-rmse:4.24549
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395822	valid-rmse:0.44039
[20]	train-rmse:0.342521	valid-rmse:0.390425
[30]	train-rmse:0.333882	valid-rmse:0.384456
[39]	train-rmse:0.330578	valid-rmse:0.383016
Iteration No: 222 ended. Search finished for the next optimal point.
Time taken: 12.2574
Function value obtained: 0.3830
Current minimum: 0.3802
Iteration No: 223 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 175, 'eta': 0.16904711043827614, 'colsample_bytree': 0.76061930465706462, 'max_depth': 152, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99114	valid-rmse:5.00868
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.86001	valid-rmse:0.888124
[20]	train-rmse:0.362444	valid-rmse:0.410404
[30]	train-rmse:0.334206	valid-rmse:0.384463
[39]	train-rmse:0.330141	valid-rmse:0.38161
Iteration No: 223 ended. Search finished for the next optimal point.
Time taken: 18.0232
Function value obtained: 0.3816
Current minimum: 0.3802
Iteration No: 224 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.27013810046603071, 'colsample_bytree': 0.68762923260259146, 'max_depth': 110, 'subsample': 1.0, 'lambda': 29.429222643617553, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.39331	valid-rmse:4.41124
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.41855	valid-rmse:0.461364
[20]	train-rmse:0.343319	valid-rmse:0.389926
[30]	train-rmse:0.335671	valid-rmse:0.383715
[39]	train-rmse:0.332289	valid-rmse:0.381647
Iteration No: 224 ended. Search finished for the next optimal point.
Time taken: 15.6612
Function value obtained: 0.3816
Current minimum: 0.3802
Iteration No: 225 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 117, 'eta': 0.18020043347332892, 'colsample_bytree': 0.67662944242575307, 'max_depth': 88, 'subsample': 1.0, 'lambda': 30.511759752041495, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9279	valid-rmse:4.94578
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.785815	valid-rmse:0.81645
[20]	train-rmse:0.366353	valid-rmse:0.413348
[30]	train-rmse:0.337324	valid-rmse:0.386868
[39]	train-rmse:0.330416	valid-rmse:0.3818
Iteration No: 225 ended. Search finished for the next optimal point.
Time taken: 13.8052
Function value obtained: 0.3818
Current minimum: 0.3802
Iteration No: 226 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.17290012950599903, 'colsample_bytree': 0.79004190473527869, 'max_depth': 148, 'subsample': 1.0, 'lambda': 18.733468629642687, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9709	valid-rmse:4.98884
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.843882	valid-rmse:0.87313
[20]	train-rmse:0.371077	valid-rmse:0.417364
[30]	train-rmse:0.337575	valid-rmse:0.386409
[39]	train-rmse:0.331175	valid-rmse:0.381336
Iteration No: 226 ended. Search finished for the next optimal point.
Time taken: 15.0943
Function value obtained: 0.3813
Current minimum: 0.3802
Iteration No: 227 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 205, 'eta': 0.17098122914977876, 'colsample_bytree': 0.99043207834313041, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97957	valid-rmse:4.99713
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.842257	valid-rmse:0.870926
[20]	train-rmse:0.361353	valid-rmse:0.409263
[30]	train-rmse:0.335328	valid-rmse:0.38507
[39]	train-rmse:0.331108	valid-rmse:0.381975
Iteration No: 227 ended. Search finished for the next optimal point.
Time taken: 21.0403
Function value obtained: 0.3820
Current minimum: 0.3802
Iteration No: 228 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 289, 'eta': 0.15895613911458525, 'colsample_bytree': 0.96725793361425316, 'max_depth': 197, 'subsample': 0.82026486226368145, 'lambda': 4.3209785447381597, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.05269	valid-rmse:5.07059
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.974395	valid-rmse:1.00111
[20]	train-rmse:0.39177	valid-rmse:0.436016
[30]	train-rmse:0.347655	valid-rmse:0.393435
[39]	train-rmse:0.341815	valid-rmse:0.387836
Iteration No: 228 ended. Search finished for the next optimal point.
Time taken: 14.9561
Function value obtained: 0.3878
Current minimum: 0.3802
Iteration No: 229 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 125, 'eta': 0.18213731145323506, 'colsample_bytree': 0.67132892309345471, 'max_depth': 84, 'subsample': 1.0, 'lambda': 29.594670034760842, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91637	valid-rmse:4.93427
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.770389	valid-rmse:0.801307
[20]	train-rmse:0.364778	valid-rmse:0.411695
[30]	train-rmse:0.336817	valid-rmse:0.385858
[39]	train-rmse:0.330376	valid-rmse:0.381243
Iteration No: 229 ended. Search finished for the next optimal point.
Time taken: 14.0402
Function value obtained: 0.3812
Current minimum: 0.3802
Iteration No: 230 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 280, 'eta': 0.26659414809693982, 'colsample_bytree': 0.97904387146783767, 'max_depth': 50, 'subsample': 0.96920561964264385, 'lambda': 86.62265969985009, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41673	valid-rmse:4.43503
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.433545	valid-rmse:0.475927
[20]	train-rmse:0.347251	valid-rmse:0.393036
[30]	train-rmse:0.337872	valid-rmse:0.385207
[39]	train-rmse:0.333867	valid-rmse:0.382508
Iteration No: 230 ended. Search finished for the next optimal point.
Time taken: 17.8051
Function value obtained: 0.3825
Current minimum: 0.3802
Iteration No: 231 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 117, 'eta': 0.25195783472866218, 'colsample_bytree': 0.8014392712082703, 'max_depth': 102, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.50398	valid-rmse:4.52224
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.460696	valid-rmse:0.50227
[20]	train-rmse:0.345443	valid-rmse:0.393315
[30]	train-rmse:0.333473	valid-rmse:0.383513
[39]	train-rmse:0.32928	valid-rmse:0.381148
Iteration No: 231 ended. Search finished for the next optimal point.
Time taken: 16.3769
Function value obtained: 0.3811
Current minimum: 0.3802
Iteration No: 232 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26879728932632352, 'colsample_bytree': 0.72027268659123633, 'max_depth': 101, 'subsample': 1.0, 'lambda': 35.420296348923195, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.40172	valid-rmse:4.41997
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.422176	valid-rmse:0.46511
[20]	train-rmse:0.344824	valid-rmse:0.391313
[30]	train-rmse:0.336043	valid-rmse:0.384105
[39]	train-rmse:0.33233	valid-rmse:0.381614
Iteration No: 232 ended. Search finished for the next optimal point.
Time taken: 15.7296
Function value obtained: 0.3816
Current minimum: 0.3802
Iteration No: 233 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 0.40000000000000002, 'max_depth': 90, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21093	valid-rmse:4.22823
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.380796	valid-rmse:0.42505
[20]	train-rmse:0.346631	valid-rmse:0.393261
[30]	train-rmse:0.340273	valid-rmse:0.388861
[39]	train-rmse:0.337475	valid-rmse:0.387369
Iteration No: 233 ended. Search finished for the next optimal point.
Time taken: 12.9364
Function value obtained: 0.3874
Current minimum: 0.3802
Iteration No: 234 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 273, 'eta': 0.29921929750542764, 'colsample_bytree': 0.99328464313475406, 'max_depth': 77, 'subsample': 0.97947105314113425, 'lambda': 89.590843581488187, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22343	valid-rmse:4.24179
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395327	valid-rmse:0.439501
[20]	train-rmse:0.345753	valid-rmse:0.392152
[30]	train-rmse:0.338353	valid-rmse:0.385758
[39]	train-rmse:0.334782	valid-rmse:0.383063
Iteration No: 234 ended. Search finished for the next optimal point.
Time taken: 17.5206
Function value obtained: 0.3831
Current minimum: 0.3802
Iteration No: 235 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 283, 'eta': 0.21252830764494676, 'colsample_bytree': 0.45583789364009386, 'max_depth': 198, 'subsample': 0.83256741514048849, 'lambda': 1.8856335667013298, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.73338	valid-rmse:4.75114
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.57147	valid-rmse:0.607053
[20]	train-rmse:0.348718	valid-rmse:0.394614
[30]	train-rmse:0.338072	valid-rmse:0.384867
[39]	train-rmse:0.334405	valid-rmse:0.382235
Iteration No: 235 ended. Search finished for the next optimal point.
Time taken: 11.6544
Function value obtained: 0.3822
Current minimum: 0.3802
Iteration No: 236 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 288, 'eta': 0.2538230337122222, 'colsample_bytree': 0.96238223702208603, 'max_depth': 72, 'subsample': 0.82479464610821829, 'lambda': 88.928435440625279, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.49308	valid-rmse:4.51135
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.460217	valid-rmse:0.501311
[20]	train-rmse:0.351617	valid-rmse:0.397624
[30]	train-rmse:0.340212	valid-rmse:0.387167
[39]	train-rmse:0.335536	valid-rmse:0.383459
Iteration No: 236 ended. Search finished for the next optimal point.
Time taken: 15.3805
Function value obtained: 0.3835
Current minimum: 0.3802
Iteration No: 237 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 27, 'eta': 0.10078678936134355, 'colsample_bytree': 0.97411270106272752, 'max_depth': 185, 'subsample': 0.90093948988009154, 'lambda': 85.143610486984841, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.40132	valid-rmse:5.41939
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.91939	valid-rmse:1.9409
[20]	train-rmse:0.767079	valid-rmse:0.799063
[30]	train-rmse:0.439789	valid-rmse:0.483543
[39]	train-rmse:0.366482	valid-rmse:0.414791
Iteration No: 237 ended. Search finished for the next optimal point.
Time taken: 12.4614
Function value obtained: 0.4148
Current minimum: 0.3802
Iteration No: 238 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.25451947046684659, 'colsample_bytree': 1.0, 'max_depth': 99, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.48846	valid-rmse:4.50672
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.453867	valid-rmse:0.495406
[20]	train-rmse:0.345988	valid-rmse:0.392827
[30]	train-rmse:0.335478	valid-rmse:0.384424
[39]	train-rmse:0.331058	valid-rmse:0.381756
Iteration No: 238 ended. Search finished for the next optimal point.
Time taken: 19.1784
Function value obtained: 0.3818
Current minimum: 0.3802
Iteration No: 239 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 12, 'eta': 0.2188323925410387, 'colsample_bytree': 0.96355721978920006, 'max_depth': 192, 'subsample': 0.90237433639665665, 'lambda': 86.92029635079588, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.70033	valid-rmse:4.7185
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.563993	valid-rmse:0.601757
[20]	train-rmse:0.349365	valid-rmse:0.399976
[30]	train-rmse:0.331754	valid-rmse:0.386658
[39]	train-rmse:0.325602	valid-rmse:0.38383
Iteration No: 239 ended. Search finished for the next optimal point.
Time taken: 22.5885
Function value obtained: 0.3838
Current minimum: 0.3802
Iteration No: 240 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 143, 'eta': 0.2745783403504124, 'colsample_bytree': 0.79386438317912411, 'max_depth': 107, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.36976	valid-rmse:4.38809
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.42018	valid-rmse:0.463585
[20]	train-rmse:0.342829	valid-rmse:0.390393
[30]	train-rmse:0.333422	valid-rmse:0.383208
[39]	train-rmse:0.329249	valid-rmse:0.380863
Iteration No: 240 ended. Search finished for the next optimal point.
Time taken: 18.0200
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 241 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 144, 'eta': 0.27438966189325587, 'colsample_bytree': 0.79485703143429531, 'max_depth': 107, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.37088	valid-rmse:4.3892
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.420464	valid-rmse:0.46385
[20]	train-rmse:0.343656	valid-rmse:0.391711
[30]	train-rmse:0.333757	valid-rmse:0.384099
[39]	train-rmse:0.329714	valid-rmse:0.382055
Iteration No: 241 ended. Search finished for the next optimal point.
Time taken: 17.4551
Function value obtained: 0.3821
Current minimum: 0.3802
Iteration No: 242 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.24596142828984566, 'colsample_bytree': 1.0, 'max_depth': 102, 'subsample': 1.0, 'lambda': 52.066645646264867, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.53774	valid-rmse:4.55605
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.471196	valid-rmse:0.511909
[20]	train-rmse:0.347643	valid-rmse:0.393622
[30]	train-rmse:0.337933	valid-rmse:0.385238
[39]	train-rmse:0.333601	valid-rmse:0.382144
Iteration No: 242 ended. Search finished for the next optimal point.
Time taken: 18.5861
Function value obtained: 0.3821
Current minimum: 0.3802
Iteration No: 243 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 181, 'eta': 0.19223052508944036, 'colsample_bytree': 0.91396030543525242, 'max_depth': 200, 'subsample': 1.0, 'lambda': 38.632194726440815, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85656	valid-rmse:4.87476
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.699975	valid-rmse:0.732837
[20]	train-rmse:0.35903	valid-rmse:0.405292
[30]	train-rmse:0.337444	valid-rmse:0.385443
[39]	train-rmse:0.331623	valid-rmse:0.3812
Iteration No: 243 ended. Search finished for the next optimal point.
Time taken: 16.8820
Function value obtained: 0.3812
Current minimum: 0.3802
Iteration No: 244 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 94, 'eta': 0.17911679848614978, 'colsample_bytree': 0.64721171801998967, 'max_depth': 80, 'subsample': 1.0, 'lambda': 33.418158032746341, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93454	valid-rmse:4.95264
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.795625	valid-rmse:0.826013
[20]	train-rmse:0.367879	valid-rmse:0.414652
[30]	train-rmse:0.336191	valid-rmse:0.386254
[39]	train-rmse:0.329242	valid-rmse:0.381152
Iteration No: 244 ended. Search finished for the next optimal point.
Time taken: 14.6400
Function value obtained: 0.3812
Current minimum: 0.3802
Iteration No: 245 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26955083340408914, 'colsample_bytree': 0.76726047792958574, 'max_depth': 101, 'subsample': 1.0, 'lambda': 42.579682457678402, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.39753	valid-rmse:4.41583
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.422447	valid-rmse:0.465132
[20]	train-rmse:0.344286	valid-rmse:0.390404
[30]	train-rmse:0.335822	valid-rmse:0.383532
[39]	train-rmse:0.332571	valid-rmse:0.381592
Iteration No: 245 ended. Search finished for the next optimal point.
Time taken: 16.4617
Function value obtained: 0.3816
Current minimum: 0.3802
Iteration No: 246 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 178, 'eta': 0.19072872875581381, 'colsample_bytree': 0.89571896761338032, 'max_depth': 200, 'subsample': 1.0, 'lambda': 37.249624440702007, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86544	valid-rmse:4.88364
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.709757	valid-rmse:0.742243
[20]	train-rmse:0.360042	valid-rmse:0.406643
[30]	train-rmse:0.337967	valid-rmse:0.386316
[39]	train-rmse:0.332315	valid-rmse:0.381921
Iteration No: 246 ended. Search finished for the next optimal point.
Time taken: 17.0749
Function value obtained: 0.3819
Current minimum: 0.3802
Iteration No: 247 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 153, 'eta': 0.17596262296176876, 'colsample_bytree': 0.48490687912864205, 'max_depth': 76, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95022	valid-rmse:4.96777
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.798849	valid-rmse:0.828405
[20]	train-rmse:0.356589	valid-rmse:0.404628
[30]	train-rmse:0.333789	valid-rmse:0.38392
[39]	train-rmse:0.329565	valid-rmse:0.38084
Iteration No: 247 ended. Search finished for the next optimal point.
Time taken: 15.2712
Function value obtained: 0.3808
Current minimum: 0.3802
Iteration No: 248 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 295, 'eta': 0.29640915904278908, 'colsample_bytree': 0.40752979098885111, 'max_depth': 78, 'subsample': 0.97681486515063309, 'lambda': 76.8618517157594, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.24004	valid-rmse:4.25852
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.403485	valid-rmse:0.447003
[20]	train-rmse:0.349186	valid-rmse:0.395363
[30]	train-rmse:0.338593	valid-rmse:0.386472
[39]	train-rmse:0.334471	valid-rmse:0.383513
Iteration No: 248 ended. Search finished for the next optimal point.
Time taken: 11.9917
Function value obtained: 0.3835
Current minimum: 0.3802
Iteration No: 249 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 237, 'eta': 0.14731563618298033, 'colsample_bytree': 0.40749661369885348, 'max_depth': 108, 'subsample': 0.87587883135671507, 'lambda': 3.487662646195107, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.12222	valid-rmse:5.14002
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.11323	valid-rmse:1.13827
[20]	train-rmse:0.41897	valid-rmse:0.46196
[30]	train-rmse:0.34675	valid-rmse:0.393745
[39]	train-rmse:0.337803	valid-rmse:0.385448
Iteration No: 249 ended. Search finished for the next optimal point.
Time taken: 11.0629
Function value obtained: 0.3854
Current minimum: 0.3802
Iteration No: 250 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.22751309040924877, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 42.545667093646856, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.64698	valid-rmse:4.66524
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.524849	valid-rmse:0.563402
[20]	train-rmse:0.349081	valid-rmse:0.395381
[30]	train-rmse:0.337143	valid-rmse:0.384672
[39]	train-rmse:0.333337	valid-rmse:0.382073
Iteration No: 250 ended. Search finished for the next optimal point.
Time taken: 18.8030
Function value obtained: 0.3821
Current minimum: 0.3802
Iteration No: 251 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 147, 'eta': 0.23710991894947783, 'colsample_bytree': 1.0, 'max_depth': 97, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.59173	valid-rmse:4.60996
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.499376	valid-rmse:0.538999
[20]	train-rmse:0.34911	valid-rmse:0.396181
[30]	train-rmse:0.336325	valid-rmse:0.385384
[39]	train-rmse:0.33154	valid-rmse:0.382352
Iteration No: 251 ended. Search finished for the next optimal point.
Time taken: 18.8929
Function value obtained: 0.3824
Current minimum: 0.3802
Iteration No: 252 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 31, 'eta': 0.19267907966612718, 'colsample_bytree': 0.40775136841246207, 'max_depth': 198, 'subsample': 0.80937510845532457, 'lambda': 83.351660704868806, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85602	valid-rmse:4.87428
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.710069	valid-rmse:0.743784
[20]	train-rmse:0.36986	valid-rmse:0.417134
[30]	train-rmse:0.340354	valid-rmse:0.390812
[39]	train-rmse:0.332503	valid-rmse:0.385027
Iteration No: 252 ended. Search finished for the next optimal point.
Time taken: 11.7559
Function value obtained: 0.3850
Current minimum: 0.3802
Iteration No: 253 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 11, 'eta': 0.13527676622351847, 'colsample_bytree': 0.46489932341444773, 'max_depth': 64, 'subsample': 0.86528245144532401, 'lambda': 0.78010012659426864, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.19346	valid-rmse:5.21126
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.27071	valid-rmse:1.2949
[20]	train-rmse:0.449005	valid-rmse:0.497437
[30]	train-rmse:0.334154	valid-rmse:0.396519
[39]	train-rmse:0.322172	valid-rmse:0.387388
Iteration No: 253 ended. Search finished for the next optimal point.
Time taken: 18.2425
Function value obtained: 0.3874
Current minimum: 0.3802
Iteration No: 254 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 168, 'eta': 0.29999999999999999, 'colsample_bytree': 0.72975637439576924, 'max_depth': 121, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21908	valid-rmse:4.23747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.393041	valid-rmse:0.43756
[20]	train-rmse:0.342012	valid-rmse:0.389163
[30]	train-rmse:0.33356	valid-rmse:0.383089
[39]	train-rmse:0.329966	valid-rmse:0.381038
Iteration No: 254 ended. Search finished for the next optimal point.
Time taken: 17.6149
Function value obtained: 0.3810
Current minimum: 0.3802
Iteration No: 255 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.27401034650455713, 'colsample_bytree': 0.75901799182366703, 'max_depth': 101, 'subsample': 1.0, 'lambda': 45.620545100631638, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.37119	valid-rmse:4.3895
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.417545	valid-rmse:0.460569
[20]	train-rmse:0.344986	valid-rmse:0.391017
[30]	train-rmse:0.336306	valid-rmse:0.384009
[39]	train-rmse:0.333002	valid-rmse:0.381874
Iteration No: 255 ended. Search finished for the next optimal point.
Time taken: 17.6222
Function value obtained: 0.3819
Current minimum: 0.3802
Iteration No: 256 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.17828198556673713, 'colsample_bytree': 0.56425923449859627, 'max_depth': 76, 'subsample': 1.0, 'lambda': 43.09470383602519, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9398	valid-rmse:4.95792
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.805229	valid-rmse:0.836098
[20]	train-rmse:0.368727	valid-rmse:0.417916
[30]	train-rmse:0.332248	valid-rmse:0.387664
[39]	train-rmse:0.323553	valid-rmse:0.382715
Iteration No: 256 ended. Search finished for the next optimal point.
Time taken: 16.9246
Function value obtained: 0.3827
Current minimum: 0.3802
Iteration No: 257 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 166, 'eta': 0.16663189857303182, 'colsample_bytree': 0.75393255759464206, 'max_depth': 151, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00553	valid-rmse:5.02308
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.882829	valid-rmse:0.910755
[20]	train-rmse:0.365392	valid-rmse:0.413075
[30]	train-rmse:0.334139	valid-rmse:0.384364
[39]	train-rmse:0.329825	valid-rmse:0.381176
Iteration No: 257 ended. Search finished for the next optimal point.
Time taken: 19.9132
Function value obtained: 0.3812
Current minimum: 0.3802
Iteration No: 258 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 159, 'eta': 0.17810384456441702, 'colsample_bytree': 0.5063132916013694, 'max_depth': 73, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93723	valid-rmse:4.95475
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.779651	valid-rmse:0.809855
[20]	train-rmse:0.354266	valid-rmse:0.403017
[30]	train-rmse:0.332566	valid-rmse:0.383428
[39]	train-rmse:0.328815	valid-rmse:0.380929
Iteration No: 258 ended. Search finished for the next optimal point.
Time taken: 16.0451
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 259 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 296, 'eta': 0.15950106625698457, 'colsample_bytree': 0.41523315288166884, 'max_depth': 8, 'subsample': 0.85014638637174667, 'lambda': 89.031256863802554, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.05294	valid-rmse:5.07115
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.993485	valid-rmse:1.02151
[20]	train-rmse:0.419212	valid-rmse:0.461757
[30]	train-rmse:0.364481	valid-rmse:0.408834
[39]	train-rmse:0.356268	valid-rmse:0.400595
Iteration No: 259 ended. Search finished for the next optimal point.
Time taken: 7.7544
Function value obtained: 0.4006
Current minimum: 0.3802
Iteration No: 260 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.27628084532636732, 'colsample_bytree': 0.77125046050541424, 'max_depth': 104, 'subsample': 1.0, 'lambda': 47.866639494854958, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.35781	valid-rmse:4.37613
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.41294	valid-rmse:0.456535
[20]	train-rmse:0.34482	valid-rmse:0.391909
[30]	train-rmse:0.336297	valid-rmse:0.385059
[39]	train-rmse:0.332749	valid-rmse:0.382885
Iteration No: 260 ended. Search finished for the next optimal point.
Time taken: 17.3765
Function value obtained: 0.3829
Current minimum: 0.3802
Iteration No: 261 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
/Users/graham/anaconda/lib/python3.6/site-packages/skopt/optimizer/optimizer.py:366: UserWarning: The objective has been evaluated at this point before.
  warnings.warn("The objective has been evaluated "
[0]	train-rmse:4.21883	valid-rmse:4.2372
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395799	valid-rmse:0.440293
[20]	train-rmse:0.344577	valid-rmse:0.391066
[30]	train-rmse:0.336463	valid-rmse:0.384766
[39]	train-rmse:0.333151	valid-rmse:0.382692
Iteration No: 261 ended. Search finished for the next optimal point.
Time taken: 20.0598
Function value obtained: 0.3827
Current minimum: 0.3802
Iteration No: 262 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 161, 'eta': 0.29999999999999999, 'colsample_bytree': 0.72126203324997684, 'max_depth': 123, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21908	valid-rmse:4.23747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.393097	valid-rmse:0.43807
[20]	train-rmse:0.34162	valid-rmse:0.389406
[30]	train-rmse:0.333119	valid-rmse:0.383117
[39]	train-rmse:0.329223	valid-rmse:0.380932
Iteration No: 262 ended. Search finished for the next optimal point.
Time taken: 17.7415
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 263 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.24547093562790059, 'colsample_bytree': 0.4136818584724839, 'max_depth': 63, 'subsample': 0.80503230777204449, 'lambda': 1.8804013600942124, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.53724	valid-rmse:4.55498
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.459034	valid-rmse:0.499669
[20]	train-rmse:0.350504	valid-rmse:0.395873
[30]	train-rmse:0.34314	valid-rmse:0.389073
[39]	train-rmse:0.340671	valid-rmse:0.387006
Iteration No: 263 ended. Search finished for the next optimal point.
Time taken: 11.6957
Function value obtained: 0.3870
Current minimum: 0.3802
Iteration No: 264 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 139, 'eta': 0.27529662103003072, 'colsample_bytree': 0.77325728004975636, 'max_depth': 109, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.3655	valid-rmse:4.38383
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.419612	valid-rmse:0.462987
[20]	train-rmse:0.34338	valid-rmse:0.390964
[30]	train-rmse:0.333777	valid-rmse:0.383767
[39]	train-rmse:0.329566	valid-rmse:0.38139
Iteration No: 264 ended. Search finished for the next optimal point.
Time taken: 17.4179
Function value obtained: 0.3814
Current minimum: 0.3802
Iteration No: 265 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 20, 'eta': 0.18899395013982942, 'colsample_bytree': 0.40051739921381996, 'max_depth': 198, 'subsample': 0.82230591062890346, 'lambda': 23.06954124427622, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87545	valid-rmse:4.89344
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.723378	valid-rmse:0.755761
[20]	train-rmse:0.362924	valid-rmse:0.41231
[30]	train-rmse:0.334046	valid-rmse:0.388735
[39]	train-rmse:0.326564	valid-rmse:0.384581
Iteration No: 265 ended. Search finished for the next optimal point.
Time taken: 13.9069
Function value obtained: 0.3846
Current minimum: 0.3802
Iteration No: 266 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 38, 'eta': 0.299218879508866, 'colsample_bytree': 0.97450982440643474, 'max_depth': 199, 'subsample': 0.88726333614784381, 'lambda': 46.610310297171672, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2215	valid-rmse:4.23992
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.385013	valid-rmse:0.430958
[20]	train-rmse:0.336115	valid-rmse:0.388907
[30]	train-rmse:0.328892	valid-rmse:0.385633
[39]	train-rmse:0.326384	valid-rmse:0.385886
Iteration No: 266 ended. Search finished for the next optimal point.
Time taken: 30.9491
Function value obtained: 0.3859
Current minimum: 0.3802
Iteration No: 267 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 166, 'eta': 0.18637066628042792, 'colsample_bytree': 0.85363338030256564, 'max_depth': 200, 'subsample': 1.0, 'lambda': 32.842394218034428, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89121	valid-rmse:4.9094
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.739244	valid-rmse:0.77086
[20]	train-rmse:0.362424	valid-rmse:0.408618
[30]	train-rmse:0.337471	valid-rmse:0.38561
[39]	train-rmse:0.331247	valid-rmse:0.381077
Iteration No: 267 ended. Search finished for the next optimal point.
Time taken: 17.4438
Function value obtained: 0.3811
Current minimum: 0.3802
Iteration No: 268 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.18084659898162989, 'colsample_bytree': 0.65437781798586858, 'max_depth': 78, 'subsample': 1.0, 'lambda': 26.116060288051347, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92392	valid-rmse:4.94184
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.7798	valid-rmse:0.810392
[20]	train-rmse:0.365086	valid-rmse:0.411386
[30]	train-rmse:0.336441	valid-rmse:0.385437
[39]	train-rmse:0.329903	valid-rmse:0.380535
Iteration No: 268 ended. Search finished for the next optimal point.
Time taken: 14.8014
Function value obtained: 0.3805
Current minimum: 0.3802
Iteration No: 269 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.17103253041891384, 'colsample_bytree': 0.41742284160618581, 'max_depth': 98, 'subsample': 0.81182058819013436, 'lambda': 87.121886810753551, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98456	valid-rmse:5.00279
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.878788	valid-rmse:0.908763
[20]	train-rmse:0.392394	valid-rmse:0.438072
[30]	train-rmse:0.344499	valid-rmse:0.394518
[39]	train-rmse:0.333837	valid-rmse:0.386439
Iteration No: 269 ended. Search finished for the next optimal point.
Time taken: 12.7464
Function value obtained: 0.3864
Current minimum: 0.3802
Iteration No: 270 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 17, 'eta': 0.23004560987315317, 'colsample_bytree': 0.40084943546076884, 'max_depth': 21, 'subsample': 0.88516724466778496, 'lambda': 42.926920063445543, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.63253	valid-rmse:4.65091
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.521403	valid-rmse:0.560625
[20]	train-rmse:0.348318	valid-rmse:0.398576
[30]	train-rmse:0.331656	valid-rmse:0.386364
[39]	train-rmse:0.327327	valid-rmse:0.384128
Iteration No: 270 ended. Search finished for the next optimal point.
Time taken: 12.2402
Function value obtained: 0.3841
Current minimum: 0.3802
Iteration No: 271 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 163, 'eta': 0.2116179740422931, 'colsample_bytree': 0.79557334780006439, 'max_depth': 83, 'subsample': 1.0, 'lambda': 49.971011546584698, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.74188	valid-rmse:4.76007
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.592521	valid-rmse:0.628456
[20]	train-rmse:0.352537	valid-rmse:0.399436
[30]	train-rmse:0.336373	valid-rmse:0.385158
[39]	train-rmse:0.331232	valid-rmse:0.381694
Iteration No: 271 ended. Search finished for the next optimal point.
Time taken: 17.0396
Function value obtained: 0.3817
Current minimum: 0.3802
Iteration No: 272 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.18032208034182493, 'colsample_bytree': 0.40000000000000002, 'max_depth': 65, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92422	valid-rmse:4.94177
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.765362	valid-rmse:0.795883
[20]	train-rmse:0.356023	valid-rmse:0.404674
[30]	train-rmse:0.334393	valid-rmse:0.38519
[39]	train-rmse:0.329677	valid-rmse:0.382192
Iteration No: 272 ended. Search finished for the next optimal point.
Time taken: 14.3007
Function value obtained: 0.3822
Current minimum: 0.3802
Iteration No: 273 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.16808321913941648, 'colsample_bytree': 0.75360502941800722, 'max_depth': 154, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99689	valid-rmse:5.01444
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.869241	valid-rmse:0.897444
[20]	train-rmse:0.363701	valid-rmse:0.41138
[30]	train-rmse:0.334346	valid-rmse:0.384391
[39]	train-rmse:0.330369	valid-rmse:0.381612
Iteration No: 273 ended. Search finished for the next optimal point.
Time taken: 20.2744
Function value obtained: 0.3816
Current minimum: 0.3802
Iteration No: 274 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 11, 'eta': 0.29964034794683447, 'colsample_bytree': 0.45460160289912521, 'max_depth': 133, 'subsample': 0.98541629208216852, 'lambda': 8.337434688078206, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2159	valid-rmse:4.23379
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.376492	valid-rmse:0.428538
[20]	train-rmse:0.330126	valid-rmse:0.394257
[30]	train-rmse:0.326178	valid-rmse:0.393767
[39]	train-rmse:0.325374	valid-rmse:0.393962
Iteration No: 274 ended. Search finished for the next optimal point.
Time taken: 26.5076
Function value obtained: 0.3940
Current minimum: 0.3802
Iteration No: 275 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 185, 'eta': 0.17159788394006642, 'colsample_bytree': 0.85095795918634543, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97591	valid-rmse:4.99343
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.836168	valid-rmse:0.865083
[20]	train-rmse:0.360157	valid-rmse:0.40838
[30]	train-rmse:0.334322	valid-rmse:0.384439
[39]	train-rmse:0.330055	valid-rmse:0.381277
Iteration No: 275 ended. Search finished for the next optimal point.
Time taken: 21.8270
Function value obtained: 0.3813
Current minimum: 0.3802
Iteration No: 276 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.23469250462740465, 'colsample_bytree': 0.73269504445359601, 'max_depth': 94, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.60635	valid-rmse:4.62457
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.506018	valid-rmse:0.546233
[20]	train-rmse:0.344959	valid-rmse:0.395708
[30]	train-rmse:0.329948	valid-rmse:0.385378
[39]	train-rmse:0.323657	valid-rmse:0.382578
Iteration No: 276 ended. Search finished for the next optimal point.
Time taken: 21.6027
Function value obtained: 0.3826
Current minimum: 0.3802
Iteration No: 277 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.22705852579871061, 'colsample_bytree': 1.0, 'max_depth': 103, 'subsample': 1.0, 'lambda': 45.632411342105968, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.64979	valid-rmse:4.66805
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.526986	valid-rmse:0.5652
[20]	train-rmse:0.35021	valid-rmse:0.396174
[30]	train-rmse:0.338443	valid-rmse:0.385781
[39]	train-rmse:0.334139	valid-rmse:0.382554
Iteration No: 277 ended. Search finished for the next optimal point.
Time taken: 20.0066
Function value obtained: 0.3826
Current minimum: 0.3802
Iteration No: 278 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 279, 'eta': 0.23207877544885816, 'colsample_bytree': 0.99603018687063938, 'max_depth': 194, 'subsample': 0.88688122234174749, 'lambda': 89.862931290740036, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.62186	valid-rmse:4.64008
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.518801	valid-rmse:0.557632
[20]	train-rmse:0.354155	valid-rmse:0.399828
[30]	train-rmse:0.340821	valid-rmse:0.387293
[39]	train-rmse:0.335648	valid-rmse:0.383101
Iteration No: 278 ended. Search finished for the next optimal point.
Time taken: 18.1567
Function value obtained: 0.3831
Current minimum: 0.3802
Iteration No: 279 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 28, 'eta': 0.16230382917589836, 'colsample_bytree': 0.99658218974933799, 'max_depth': 196, 'subsample': 0.92747732154868778, 'lambda': 3.8313824740581386, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.03246	valid-rmse:5.05018
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.936233	valid-rmse:0.963931
[20]	train-rmse:0.378338	valid-rmse:0.426121
[30]	train-rmse:0.339525	valid-rmse:0.3897
[39]	train-rmse:0.334704	valid-rmse:0.385607
Iteration No: 279 ended. Search finished for the next optimal point.
Time taken: 24.4095
Function value obtained: 0.3856
Current minimum: 0.3802
Iteration No: 280 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 129, 'eta': 0.18391842178075646, 'colsample_bytree': 0.65870624880704576, 'max_depth': 74, 'subsample': 1.0, 'lambda': 29.467731528892656, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90577	valid-rmse:4.92367
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.756721	valid-rmse:0.787951
[20]	train-rmse:0.363253	valid-rmse:0.410109
[30]	train-rmse:0.336721	valid-rmse:0.38581
[39]	train-rmse:0.330281	valid-rmse:0.38116
Iteration No: 280 ended. Search finished for the next optimal point.
Time taken: 16.2492
Function value obtained: 0.3812
Current minimum: 0.3802
Iteration No: 281 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 137, 'eta': 0.1743220752734336, 'colsample_bytree': 0.80851126025584974, 'max_depth': 152, 'subsample': 1.0, 'lambda': 27.243299940396113, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96276	valid-rmse:4.98065
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.833481	valid-rmse:0.862983
[20]	train-rmse:0.371702	valid-rmse:0.417937
[30]	train-rmse:0.337721	valid-rmse:0.386626
[39]	train-rmse:0.331283	valid-rmse:0.381518
Iteration No: 281 ended. Search finished for the next optimal point.
Time taken: 17.7904
Function value obtained: 0.3815
Current minimum: 0.3802
Iteration No: 282 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 132, 'eta': 0.18390957734459443, 'colsample_bytree': 0.65857726294637886, 'max_depth': 74, 'subsample': 1.0, 'lambda': 28.556826169808662, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90578	valid-rmse:4.92368
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.756459	valid-rmse:0.787652
[20]	train-rmse:0.362972	valid-rmse:0.409786
[30]	train-rmse:0.336744	valid-rmse:0.385892
[39]	train-rmse:0.330362	valid-rmse:0.381163
Iteration No: 282 ended. Search finished for the next optimal point.
Time taken: 16.5091
Function value obtained: 0.3812
Current minimum: 0.3802
Iteration No: 283 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.18281258231726963, 'colsample_bytree': 0.65759092060262647, 'max_depth': 76, 'subsample': 1.0, 'lambda': 27.469711032761776, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91226	valid-rmse:4.93016
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.764883	valid-rmse:0.795644
[20]	train-rmse:0.364045	valid-rmse:0.410626
[30]	train-rmse:0.336898	valid-rmse:0.386011
[39]	train-rmse:0.330552	valid-rmse:0.381421
Iteration No: 283 ended. Search finished for the next optimal point.
Time taken: 16.1840
Function value obtained: 0.3814
Current minimum: 0.3802
Iteration No: 284 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 179, 'eta': 0.17978184138061332, 'colsample_bytree': 0.58085074783697954, 'max_depth': 79, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92792	valid-rmse:4.94555
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.767074	valid-rmse:0.797464
[20]	train-rmse:0.353732	valid-rmse:0.40222
[30]	train-rmse:0.334096	valid-rmse:0.384268
[39]	train-rmse:0.330559	valid-rmse:0.381765
Iteration No: 284 ended. Search finished for the next optimal point.
Time taken: 18.3478
Function value obtained: 0.3818
Current minimum: 0.3802
Iteration No: 285 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 278, 'eta': 0.29909599317897739, 'colsample_bytree': 0.43385959989417366, 'max_depth': 40, 'subsample': 0.98193927719103513, 'lambda': 2.0344747133635659, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21784	valid-rmse:4.23564
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.378051	valid-rmse:0.422971
[20]	train-rmse:0.341011	valid-rmse:0.388261
[30]	train-rmse:0.334703	valid-rmse:0.383898
[39]	train-rmse:0.332529	valid-rmse:0.383085
Iteration No: 285 ended. Search finished for the next optimal point.
Time taken: 15.2683
Function value obtained: 0.3831
Current minimum: 0.3802
Iteration No: 286 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 152, 'eta': 0.27869897873730665, 'colsample_bytree': 0.7972164000931129, 'max_depth': 109, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.34533	valid-rmse:4.36367
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.414451	valid-rmse:0.457903
[20]	train-rmse:0.343694	valid-rmse:0.391338
[30]	train-rmse:0.334274	valid-rmse:0.383963
[39]	train-rmse:0.330135	valid-rmse:0.381705
Iteration No: 286 ended. Search finished for the next optimal point.
Time taken: 19.6360
Function value obtained: 0.3817
Current minimum: 0.3802
Iteration No: 287 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 13, 'eta': 0.14081897350408309, 'colsample_bytree': 0.99439885186957999, 'max_depth': 161, 'subsample': 0.95964698382568669, 'lambda': 4.0558191319072527, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.16057	valid-rmse:5.17834
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.19441	valid-rmse:1.21902
[20]	train-rmse:0.431204	valid-rmse:0.478878
[30]	train-rmse:0.333866	valid-rmse:0.394018
[39]	train-rmse:0.322036	valid-rmse:0.385824
Iteration No: 287 ended. Search finished for the next optimal point.
Time taken: 28.9629
Function value obtained: 0.3858
Current minimum: 0.3802
Iteration No: 288 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 186, 'eta': 0.19767886288173961, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 42.219895220715031, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.82428	valid-rmse:4.84249
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.665284	valid-rmse:0.698794
[20]	train-rmse:0.356715	valid-rmse:0.403247
[30]	train-rmse:0.337967	valid-rmse:0.386211
[39]	train-rmse:0.331988	valid-rmse:0.381777
Iteration No: 288 ended. Search finished for the next optimal point.
Time taken: 19.8616
Function value obtained: 0.3818
Current minimum: 0.3802
Iteration No: 289 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 49.339551786095974, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21682	valid-rmse:4.23526
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.388313	valid-rmse:0.432921
[20]	train-rmse:0.342337	valid-rmse:0.389318
[30]	train-rmse:0.335362	valid-rmse:0.384133
[39]	train-rmse:0.33265	valid-rmse:0.382892
Iteration No: 289 ended. Search finished for the next optimal point.
Time taken: 23.4869
Function value obtained: 0.3829
Current minimum: 0.3802
Iteration No: 290 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 192, 'eta': 0.1727002171424061, 'colsample_bytree': 0.85006191330023761, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96933	valid-rmse:4.9869
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.826252	valid-rmse:0.855256
[20]	train-rmse:0.35912	valid-rmse:0.407196
[30]	train-rmse:0.334529	valid-rmse:0.38446
[39]	train-rmse:0.33044	valid-rmse:0.381499
Iteration No: 290 ended. Search finished for the next optimal point.
Time taken: 21.8453
Function value obtained: 0.3815
Current minimum: 0.3802
Iteration No: 291 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 23, 'eta': 0.17219870215496458, 'colsample_bytree': 0.40227298096978426, 'max_depth': 194, 'subsample': 0.98684901649404244, 'lambda': 84.054320380166686, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97717	valid-rmse:4.99533
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.866264	valid-rmse:0.896127
[20]	train-rmse:0.391702	valid-rmse:0.437221
[30]	train-rmse:0.345816	valid-rmse:0.395375
[39]	train-rmse:0.334023	valid-rmse:0.386163
Iteration No: 291 ended. Search finished for the next optimal point.
Time taken: 13.1026
Function value obtained: 0.3862
Current minimum: 0.3802
Iteration No: 292 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 0.71560800191760832, 'max_depth': 112, 'subsample': 1.0, 'lambda': 53.785653828246168, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21739	valid-rmse:4.23573
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.392516	valid-rmse:0.43676
[20]	train-rmse:0.343462	valid-rmse:0.390142
[30]	train-rmse:0.335621	valid-rmse:0.384101
[39]	train-rmse:0.332554	valid-rmse:0.382374
Iteration No: 292 ended. Search finished for the next optimal point.
Time taken: 18.9651
Function value obtained: 0.3824
Current minimum: 0.3802
Iteration No: 293 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 153, 'eta': 0.23905162920003051, 'colsample_bytree': 1.0, 'max_depth': 99, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.58021	valid-rmse:4.59844
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.492938	valid-rmse:0.532751
[20]	train-rmse:0.348339	valid-rmse:0.395337
[30]	train-rmse:0.335933	valid-rmse:0.385055
[39]	train-rmse:0.331143	valid-rmse:0.381827
Iteration No: 293 ended. Search finished for the next optimal point.
Time taken: 20.8212
Function value obtained: 0.3818
Current minimum: 0.3802
Iteration No: 294 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 187, 'eta': 0.19695784495493879, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 41.522423001389924, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.82854	valid-rmse:4.84675
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.67006	valid-rmse:0.703392
[20]	train-rmse:0.357868	valid-rmse:0.403938
[30]	train-rmse:0.337733	valid-rmse:0.385745
[39]	train-rmse:0.332241	valid-rmse:0.381758
Iteration No: 294 ended. Search finished for the next optimal point.
Time taken: 19.7504
Function value obtained: 0.3818
Current minimum: 0.3802
Iteration No: 295 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.1802567446495616, 'colsample_bytree': 0.40000000000000002, 'max_depth': 65, 'subsample': 1.0, 'lambda': 34.542997760603399, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92783	valid-rmse:4.94592
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.792374	valid-rmse:0.823563
[20]	train-rmse:0.370949	valid-rmse:0.420187
[30]	train-rmse:0.334132	valid-rmse:0.389945
[39]	train-rmse:0.32461	valid-rmse:0.384353
Iteration No: 295 ended. Search finished for the next optimal point.
Time taken: 15.8647
Function value obtained: 0.3844
Current minimum: 0.3802
Iteration No: 296 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 187, 'eta': 0.17211434418472818, 'colsample_bytree': 0.8318261041823678, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97284	valid-rmse:4.9904
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.831945	valid-rmse:0.860724
[20]	train-rmse:0.360023	valid-rmse:0.408133
[30]	train-rmse:0.334668	valid-rmse:0.384998
[39]	train-rmse:0.330585	valid-rmse:0.38198
Iteration No: 296 ended. Search finished for the next optimal point.
Time taken: 22.5419
Function value obtained: 0.3820
Current minimum: 0.3802
Iteration No: 297 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 151, 'eta': 0.29999999999999999, 'colsample_bytree': 0.71149828691660255, 'max_depth': 129, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21908	valid-rmse:4.23747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.393323	valid-rmse:0.438187
[20]	train-rmse:0.341475	valid-rmse:0.389662
[30]	train-rmse:0.332857	valid-rmse:0.383391
[39]	train-rmse:0.329526	valid-rmse:0.38169
Iteration No: 297 ended. Search finished for the next optimal point.
Time taken: 18.4870
Function value obtained: 0.3817
Current minimum: 0.3802
Iteration No: 298 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 22, 'eta': 0.22821528693340506, 'colsample_bytree': 0.9584812857522117, 'max_depth': 200, 'subsample': 0.91946880932536679, 'lambda': 26.865833022067804, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.64209	valid-rmse:4.6601
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.516597	valid-rmse:0.556092
[20]	train-rmse:0.339081	valid-rmse:0.392307
[30]	train-rmse:0.326755	valid-rmse:0.385056
[39]	train-rmse:0.323102	valid-rmse:0.384789
Iteration No: 298 ended. Search finished for the next optimal point.
Time taken: 30.2629
Function value obtained: 0.3848
Current minimum: 0.3802
Iteration No: 299 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 176, 'eta': 0.22038793360266393, 'colsample_bytree': 0.82898665048547671, 'max_depth': 200, 'subsample': 1.0, 'lambda': 59.989330395005631, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.69007	valid-rmse:4.70827
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.554481	valid-rmse:0.59155
[20]	train-rmse:0.350817	valid-rmse:0.397522
[30]	train-rmse:0.336367	valid-rmse:0.384908
[39]	train-rmse:0.331452	valid-rmse:0.381555
Iteration No: 299 ended. Search finished for the next optimal point.
Time taken: 18.1188
Function value obtained: 0.3816
Current minimum: 0.3802
Iteration No: 300 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 293, 'eta': 0.18890659550000055, 'colsample_bytree': 0.99285119891052387, 'max_depth': 12, 'subsample': 0.86025467316867077, 'lambda': 25.204483682640035, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87583	valid-rmse:4.89381
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.721574	valid-rmse:0.753465
[20]	train-rmse:0.36617	valid-rmse:0.411464
[30]	train-rmse:0.346989	valid-rmse:0.392452
[39]	train-rmse:0.343	valid-rmse:0.388674
Iteration No: 300 ended. Search finished for the next optimal point.
Time taken: 13.4081
Function value obtained: 0.3887
Current minimum: 0.3802
Iteration No: 301 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.20165153032205968, 'colsample_bytree': 0.71382767710190853, 'max_depth': 79, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.80052	valid-rmse:4.81792
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.620809	valid-rmse:0.654603
[20]	train-rmse:0.350226	valid-rmse:0.39723
[30]	train-rmse:0.33941	valid-rmse:0.387341
[39]	train-rmse:0.335895	valid-rmse:0.38488
Iteration No: 301 ended. Search finished for the next optimal point.
Time taken: 18.9283
Function value obtained: 0.3849
Current minimum: 0.3802
Iteration No: 302 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 296, 'eta': 0.1824732692324178, 'colsample_bytree': 0.41768204397943709, 'max_depth': 178, 'subsample': 0.80077644652862523, 'lambda': 25.412005157436056, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91442	valid-rmse:4.93242
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.773278	valid-rmse:0.804056
[20]	train-rmse:0.374928	valid-rmse:0.419507
[30]	train-rmse:0.34624	valid-rmse:0.392136
[39]	train-rmse:0.339562	valid-rmse:0.386135
Iteration No: 302 ended. Search finished for the next optimal point.
Time taken: 12.0466
Function value obtained: 0.3861
Current minimum: 0.3802
Iteration No: 303 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 124, 'eta': 0.26522370162484998, 'colsample_bytree': 0.80551073966105891, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.42532	valid-rmse:4.4436
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.434515	valid-rmse:0.477505
[20]	train-rmse:0.344408	valid-rmse:0.392358
[30]	train-rmse:0.333721	valid-rmse:0.384122
[39]	train-rmse:0.329465	valid-rmse:0.381863
Iteration No: 303 ended. Search finished for the next optimal point.
Time taken: 19.5196
Function value obtained: 0.3819
Current minimum: 0.3802
Iteration No: 304 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.25570323352651358, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 40.79145353167231, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.47944	valid-rmse:4.49776
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.445234	valid-rmse:0.487147
[20]	train-rmse:0.345449	valid-rmse:0.391772
[30]	train-rmse:0.336555	valid-rmse:0.384492
[39]	train-rmse:0.332758	valid-rmse:0.381928
Iteration No: 304 ended. Search finished for the next optimal point.
Time taken: 21.1187
Function value obtained: 0.3819
Current minimum: 0.3802
Iteration No: 305 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.17618480387567775, 'colsample_bytree': 0.81544951989522463, 'max_depth': 149, 'subsample': 1.0, 'lambda': 29.469349721527923, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95157	valid-rmse:4.96955
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.818124	valid-rmse:0.847965
[20]	train-rmse:0.370238	valid-rmse:0.415959
[30]	train-rmse:0.337358	valid-rmse:0.385636
[39]	train-rmse:0.330666	valid-rmse:0.380521
Iteration No: 305 ended. Search finished for the next optimal point.
Time taken: 18.0462
Function value obtained: 0.3805
Current minimum: 0.3802
Iteration No: 306 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 288, 'eta': 0.29840223571674251, 'colsample_bytree': 0.4467286696189634, 'max_depth': 194, 'subsample': 0.93296910780164211, 'lambda': 8.0553734735314784, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22345	valid-rmse:4.24137
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.383631	valid-rmse:0.428267
[20]	train-rmse:0.342557	valid-rmse:0.389396
[30]	train-rmse:0.33566	valid-rmse:0.384457
[39]	train-rmse:0.332631	valid-rmse:0.382646
Iteration No: 306 ended. Search finished for the next optimal point.
Time taken: 15.8525
Function value obtained: 0.3826
Current minimum: 0.3802
Iteration No: 307 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 22, 'eta': 0.26180887729746516, 'colsample_bytree': 0.95657110091960273, 'max_depth': 196, 'subsample': 0.93714013269393348, 'lambda': 89.207244860420658, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4454	valid-rmse:4.46366
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.440428	valid-rmse:0.483312
[20]	train-rmse:0.348316	valid-rmse:0.395153
[30]	train-rmse:0.340017	valid-rmse:0.387634
[39]	train-rmse:0.336718	valid-rmse:0.385219
Iteration No: 307 ended. Search finished for the next optimal point.
Time taken: 22.8755
Function value obtained: 0.3852
Current minimum: 0.3802
Iteration No: 308 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 132, 'eta': 0.17592193083848262, 'colsample_bytree': 0.81329037132115101, 'max_depth': 148, 'subsample': 1.0, 'lambda': 29.30723206990627, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95313	valid-rmse:4.97111
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.820431	valid-rmse:0.85015
[20]	train-rmse:0.370159	valid-rmse:0.416214
[30]	train-rmse:0.3377	valid-rmse:0.386277
[39]	train-rmse:0.331173	valid-rmse:0.381274
Iteration No: 308 ended. Search finished for the next optimal point.
Time taken: 18.0399
Function value obtained: 0.3813
Current minimum: 0.3802
Iteration No: 309 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 121, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21883	valid-rmse:4.2372
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395799	valid-rmse:0.440293
[20]	train-rmse:0.344577	valid-rmse:0.391066
[30]	train-rmse:0.336463	valid-rmse:0.384766
[39]	train-rmse:0.333151	valid-rmse:0.382692
Iteration No: 309 ended. Search finished for the next optimal point.
Time taken: 21.6270
Function value obtained: 0.3827
Current minimum: 0.3802
Iteration No: 310 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 238, 'eta': 0.10181079410228007, 'colsample_bytree': 0.40825799769983223, 'max_depth': 62, 'subsample': 0.87116222038897706, 'lambda': 0.34216805174001219, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.39291	valid-rmse:5.4107
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.88128	valid-rmse:1.90132
[20]	train-rmse:0.729112	valid-rmse:0.760291
[30]	train-rmse:0.412146	valid-rmse:0.455904
[39]	train-rmse:0.353532	valid-rmse:0.400822
Iteration No: 310 ended. Search finished for the next optimal point.
Time taken: 13.4433
Function value obtained: 0.4008
Current minimum: 0.3802
Iteration No: 311 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.21015923191911362, 'colsample_bytree': 0.84260415998074156, 'max_depth': 86, 'subsample': 1.0, 'lambda': 56.451133801900397, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.75057	valid-rmse:4.7688
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.599606	valid-rmse:0.634887
[20]	train-rmse:0.352907	valid-rmse:0.399372
[30]	train-rmse:0.336725	valid-rmse:0.384931
[39]	train-rmse:0.331035	valid-rmse:0.381007
Iteration No: 311 ended. Search finished for the next optimal point.
Time taken: 18.7952
Function value obtained: 0.3810
Current minimum: 0.3802
Iteration No: 312 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 158, 'eta': 0.1939988818021891, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 39.999195378642618, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84609	valid-rmse:4.86429
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.687756	valid-rmse:0.720751
[20]	train-rmse:0.357445	valid-rmse:0.404059
[30]	train-rmse:0.337229	valid-rmse:0.385754
[39]	train-rmse:0.331344	valid-rmse:0.381641
Iteration No: 312 ended. Search finished for the next optimal point.
Time taken: 20.8727
Function value obtained: 0.3816
Current minimum: 0.3802
Iteration No: 313 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 142, 'eta': 0.18714875883811594, 'colsample_bytree': 0.82849035840295437, 'max_depth': 200, 'subsample': 1.0, 'lambda': 34.947195758304616, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88665	valid-rmse:4.90484
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.734187	valid-rmse:0.766106
[20]	train-rmse:0.362661	valid-rmse:0.409135
[30]	train-rmse:0.337482	valid-rmse:0.385856
[39]	train-rmse:0.331228	valid-rmse:0.381019
Iteration No: 313 ended. Search finished for the next optimal point.
Time taken: 18.6843
Function value obtained: 0.3810
Current minimum: 0.3802
Iteration No: 314 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 285, 'eta': 0.231511684393784, 'colsample_bytree': 0.470347305257098, 'max_depth': 196, 'subsample': 0.9730134426142234, 'lambda': 86.740882245186626, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.62528	valid-rmse:4.64355
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.523322	valid-rmse:0.561947
[20]	train-rmse:0.359482	valid-rmse:0.404851
[30]	train-rmse:0.347028	valid-rmse:0.393087
[39]	train-rmse:0.342019	valid-rmse:0.388452
Iteration No: 314 ended. Search finished for the next optimal point.
Time taken: 13.4148
Function value obtained: 0.3885
Current minimum: 0.3802
Iteration No: 315 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 291, 'eta': 0.2975225087190978, 'colsample_bytree': 0.97396859242510447, 'max_depth': 24, 'subsample': 0.8755435858311349, 'lambda': 86.658456685059861, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.23375	valid-rmse:4.2521
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.397925	valid-rmse:0.441968
[20]	train-rmse:0.347513	valid-rmse:0.392913
[30]	train-rmse:0.339471	valid-rmse:0.386126
[39]	train-rmse:0.336656	valid-rmse:0.384117
Iteration No: 315 ended. Search finished for the next optimal point.
Time taken: 18.4970
Function value obtained: 0.3841
Current minimum: 0.3802
Iteration No: 316 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 270, 'eta': 0.22868472670205633, 'colsample_bytree': 0.99754492395225203, 'max_depth': 13, 'subsample': 0.95402718498033323, 'lambda': 80.15133823527789, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.64153	valid-rmse:4.65975
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.52736	valid-rmse:0.565548
[20]	train-rmse:0.355941	valid-rmse:0.401051
[30]	train-rmse:0.345916	valid-rmse:0.391329
[39]	train-rmse:0.342824	valid-rmse:0.388576
Iteration No: 316 ended. Search finished for the next optimal point.
Time taken: 14.4202
Function value obtained: 0.3886
Current minimum: 0.3802
Iteration No: 317 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 170, 'eta': 0.24316996277929662, 'colsample_bytree': 0.41690973128310177, 'max_depth': 6, 'subsample': 0.89014365876205659, 'lambda': 6.3235985156777232, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55164	valid-rmse:4.56949
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.480741	valid-rmse:0.520265
[20]	train-rmse:0.366927	valid-rmse:0.410609
[30]	train-rmse:0.356619	valid-rmse:0.400926
[39]	train-rmse:0.352274	valid-rmse:0.396693
Iteration No: 317 ended. Search finished for the next optimal point.
Time taken: 9.9137
Function value obtained: 0.3967
Current minimum: 0.3802
Iteration No: 318 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.21617032168230782, 'colsample_bytree': 0.76263833217348242, 'max_depth': 88, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.71624	valid-rmse:4.73443
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.576676	valid-rmse:0.614271
[20]	train-rmse:0.350174	valid-rmse:0.400872
[30]	train-rmse:0.330799	valid-rmse:0.386035
[39]	train-rmse:0.32423	valid-rmse:0.383059
Iteration No: 318 ended. Search finished for the next optimal point.
Time taken: 23.3236
Function value obtained: 0.3831
Current minimum: 0.3802
Iteration No: 319 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 190, 'eta': 0.17663299821320599, 'colsample_bytree': 0.79355568245454455, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94583	valid-rmse:4.96339
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.791953	valid-rmse:0.821736
[20]	train-rmse:0.355691	valid-rmse:0.403705
[30]	train-rmse:0.334455	valid-rmse:0.384172
[39]	train-rmse:0.33053	valid-rmse:0.381482
Iteration No: 319 ended. Search finished for the next optimal point.
Time taken: 23.9228
Function value obtained: 0.3815
Current minimum: 0.3802
Iteration No: 320 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 95, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21883	valid-rmse:4.2372
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395799	valid-rmse:0.440293
[20]	train-rmse:0.344577	valid-rmse:0.391066
[30]	train-rmse:0.336463	valid-rmse:0.384766
[39]	train-rmse:0.333151	valid-rmse:0.382692
Iteration No: 320 ended. Search finished for the next optimal point.
Time taken: 24.0650
Function value obtained: 0.3827
Current minimum: 0.3802
Iteration No: 321 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 12, 'eta': 0.28483974958264663, 'colsample_bytree': 0.43575488419953218, 'max_depth': 199, 'subsample': 0.99682565243018584, 'lambda': 87.415944161777844, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.30898	valid-rmse:4.3274
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.410797	valid-rmse:0.456137
[20]	train-rmse:0.340135	valid-rmse:0.392892
[30]	train-rmse:0.327923	valid-rmse:0.385425
[39]	train-rmse:0.323217	valid-rmse:0.383778
Iteration No: 321 ended. Search finished for the next optimal point.
Time taken: 19.7409
Function value obtained: 0.3838
Current minimum: 0.3802
Iteration No: 322 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 163, 'eta': 0.17042305837284802, 'colsample_bytree': 0.6630481923333178, 'max_depth': 116, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98289	valid-rmse:5.00045
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.846875	valid-rmse:0.875379
[20]	train-rmse:0.360502	valid-rmse:0.40859
[30]	train-rmse:0.333484	valid-rmse:0.383786
[39]	train-rmse:0.329438	valid-rmse:0.380892
Iteration No: 322 ended. Search finished for the next optimal point.
Time taken: 22.3195
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 323 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 296, 'eta': 0.18906616491136852, 'colsample_bytree': 0.99245255925822617, 'max_depth': 56, 'subsample': 0.97473137583267822, 'lambda': 89.791801965099793, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87691	valid-rmse:4.89506
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.73022	valid-rmse:0.762418
[20]	train-rmse:0.37076	valid-rmse:0.416158
[30]	train-rmse:0.344982	valid-rmse:0.391344
[39]	train-rmse:0.337623	valid-rmse:0.384779
Iteration No: 323 ended. Search finished for the next optimal point.
Time taken: 19.4656
Function value obtained: 0.3848
Current minimum: 0.3802
Iteration No: 324 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 158, 'eta': 0.20315688870833901, 'colsample_bytree': 0.82527669440103102, 'max_depth': 83, 'subsample': 1.0, 'lambda': 49.574945186622308, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.79195	valid-rmse:4.81017
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.635974	valid-rmse:0.670205
[20]	train-rmse:0.355821	valid-rmse:0.401916
[30]	train-rmse:0.337069	valid-rmse:0.384967
[39]	train-rmse:0.331241	valid-rmse:0.380882
Iteration No: 324 ended. Search finished for the next optimal point.
Time taken: 20.5591
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 325 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 0.69816347830845937, 'max_depth': 100, 'subsample': 1.0, 'lambda': 51.250414025050631, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21722	valid-rmse:4.2356
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.390942	valid-rmse:0.435444
[20]	train-rmse:0.343537	valid-rmse:0.390473
[30]	train-rmse:0.335635	valid-rmse:0.384363
[39]	train-rmse:0.33252	valid-rmse:0.382591
Iteration No: 325 ended. Search finished for the next optimal point.
Time taken: 19.9326
Function value obtained: 0.3826
Current minimum: 0.3802
Iteration No: 326 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.23182334551835426, 'colsample_bytree': 1.0, 'max_depth': 89, 'subsample': 1.0, 'lambda': 51.172286348571255, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.62168	valid-rmse:4.63996
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.511449	valid-rmse:0.550425
[20]	train-rmse:0.349909	valid-rmse:0.396343
[30]	train-rmse:0.338072	valid-rmse:0.38552
[39]	train-rmse:0.333561	valid-rmse:0.382189
Iteration No: 326 ended. Search finished for the next optimal point.
Time taken: 22.9839
Function value obtained: 0.3822
Current minimum: 0.3802
Iteration No: 327 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.17495125399685049, 'colsample_bytree': 0.62742877402078168, 'max_depth': 94, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95763	valid-rmse:4.9752
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.808487	valid-rmse:0.837755
[20]	train-rmse:0.359898	valid-rmse:0.407628
[30]	train-rmse:0.337193	valid-rmse:0.386682
[39]	train-rmse:0.333188	valid-rmse:0.383751
Iteration No: 327 ended. Search finished for the next optimal point.
Time taken: 20.4913
Function value obtained: 0.3838
Current minimum: 0.3802
Iteration No: 328 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 0.75064004613194979, 'max_depth': 200, 'subsample': 1.0, 'lambda': 43.731587968652086, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21686	valid-rmse:4.23524
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.388137	valid-rmse:0.432674
[20]	train-rmse:0.342438	valid-rmse:0.389116
[30]	train-rmse:0.335656	valid-rmse:0.384065
[39]	train-rmse:0.332616	valid-rmse:0.382202
Iteration No: 328 ended. Search finished for the next optimal point.
Time taken: 21.4606
Function value obtained: 0.3822
Current minimum: 0.3802
Iteration No: 329 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 265, 'eta': 0.1428701717857021, 'colsample_bytree': 0.40666991388062546, 'max_depth': 5, 'subsample': 0.91497370084568264, 'lambda': 0.30725279236161435, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.14838	valid-rmse:5.16613
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.17596	valid-rmse:1.20037
[20]	train-rmse:0.456904	valid-rmse:0.497172
[30]	train-rmse:0.37893	valid-rmse:0.421961
[39]	train-rmse:0.36874	valid-rmse:0.411804
Iteration No: 329 ended. Search finished for the next optimal point.
Time taken: 10.2646
Function value obtained: 0.4118
Current minimum: 0.3802
Iteration No: 330 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 159, 'eta': 0.2003053492007848, 'colsample_bytree': 0.74843087379648887, 'max_depth': 59, 'subsample': 1.0, 'lambda': 37.597233579819125, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.80871	valid-rmse:4.82687
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.649255	valid-rmse:0.683477
[20]	train-rmse:0.354809	valid-rmse:0.401798
[30]	train-rmse:0.336301	valid-rmse:0.384979
[39]	train-rmse:0.330771	valid-rmse:0.380764
Iteration No: 330 ended. Search finished for the next optimal point.
Time taken: 18.5685
Function value obtained: 0.3808
Current minimum: 0.3802
Iteration No: 331 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.22142164333605738, 'colsample_bytree': 1.0, 'max_depth': 67, 'subsample': 1.0, 'lambda': 41.416812737078793, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.68314	valid-rmse:4.70139
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.547762	valid-rmse:0.585162
[20]	train-rmse:0.35084	valid-rmse:0.396557
[30]	train-rmse:0.338771	valid-rmse:0.385698
[39]	train-rmse:0.334169	valid-rmse:0.382124
Iteration No: 331 ended. Search finished for the next optimal point.
Time taken: 21.7931
Function value obtained: 0.3821
Current minimum: 0.3802
Iteration No: 332 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 144, 'eta': 0.19769010824583905, 'colsample_bytree': 0.72409240033500011, 'max_depth': 59, 'subsample': 1.0, 'lambda': 37.159581407860216, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.82423	valid-rmse:4.84237
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.664982	valid-rmse:0.698704
[20]	train-rmse:0.356283	valid-rmse:0.402963
[30]	train-rmse:0.336179	valid-rmse:0.384811
[39]	train-rmse:0.330819	valid-rmse:0.38099
Iteration No: 332 ended. Search finished for the next optimal point.
Time taken: 20.0944
Function value obtained: 0.3810
Current minimum: 0.3802
Iteration No: 333 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 144, 'eta': 0.19732272033908166, 'colsample_bytree': 0.72295970831592005, 'max_depth': 59, 'subsample': 1.0, 'lambda': 36.968226706887293, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.82641	valid-rmse:4.84454
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.666851	valid-rmse:0.700551
[20]	train-rmse:0.355869	valid-rmse:0.402798
[30]	train-rmse:0.335693	valid-rmse:0.384651
[39]	train-rmse:0.330657	valid-rmse:0.381323
Iteration No: 333 ended. Search finished for the next optimal point.
Time taken: 18.9932
Function value obtained: 0.3813
Current minimum: 0.3802
Iteration No: 334 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 144, 'eta': 0.19679965274940475, 'colsample_bytree': 0.72100669035287801, 'max_depth': 59, 'subsample': 1.0, 'lambda': 36.212845389909766, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8295	valid-rmse:4.84763
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.670618	valid-rmse:0.704146
[20]	train-rmse:0.356704	valid-rmse:0.403796
[30]	train-rmse:0.336122	valid-rmse:0.385296
[39]	train-rmse:0.330445	valid-rmse:0.381178
Iteration No: 334 ended. Search finished for the next optimal point.
Time taken: 19.5665
Function value obtained: 0.3812
Current minimum: 0.3802
Iteration No: 335 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 205, 'eta': 0.26319823701280642, 'colsample_bytree': 1.0, 'max_depth': 81, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.43702	valid-rmse:4.45529
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.437935	valid-rmse:0.480309
[20]	train-rmse:0.346087	valid-rmse:0.392999
[30]	train-rmse:0.335957	valid-rmse:0.384928
[39]	train-rmse:0.331815	valid-rmse:0.382029
Iteration No: 335 ended. Search finished for the next optimal point.
Time taken: 24.5792
Function value obtained: 0.3820
Current minimum: 0.3802
Iteration No: 336 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 297, 'eta': 0.29837602499921967, 'colsample_bytree': 0.40756010449615176, 'max_depth': 50, 'subsample': 0.86250925263300071, 'lambda': 44.707098567231718, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22707	valid-rmse:4.24568
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.397661	valid-rmse:0.440865
[20]	train-rmse:0.347782	valid-rmse:0.393609
[30]	train-rmse:0.338406	valid-rmse:0.385796
[39]	train-rmse:0.334645	valid-rmse:0.383249
Iteration No: 336 ended. Search finished for the next optimal point.
Time taken: 15.9377
Function value obtained: 0.3832
Current minimum: 0.3802
Iteration No: 337 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.19154446537587619, 'colsample_bytree': 0.86416096823091471, 'max_depth': 173, 'subsample': 1.0, 'lambda': 37.83208036601345, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86061	valid-rmse:4.87881
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.704152	valid-rmse:0.736908
[20]	train-rmse:0.359219	valid-rmse:0.4058
[30]	train-rmse:0.33679	valid-rmse:0.385154
[39]	train-rmse:0.331175	valid-rmse:0.381209
Iteration No: 337 ended. Search finished for the next optimal point.
Time taken: 21.3176
Function value obtained: 0.3812
Current minimum: 0.3802
Iteration No: 338 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.18771639931699619, 'colsample_bytree': 0.59505726199549192, 'max_depth': 59, 'subsample': 1.0, 'lambda': 47.847169522066963, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88379	valid-rmse:4.90193
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.734222	valid-rmse:0.766895
[20]	train-rmse:0.361368	valid-rmse:0.411678
[30]	train-rmse:0.331615	valid-rmse:0.387895
[39]	train-rmse:0.323569	valid-rmse:0.383509
Iteration No: 338 ended. Search finished for the next optimal point.
Time taken: 20.9659
Function value obtained: 0.3835
Current minimum: 0.3802
Iteration No: 339 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.19282626627972926, 'colsample_bytree': 0.87860500438402223, 'max_depth': 172, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84917	valid-rmse:4.86669
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.672991	valid-rmse:0.705671
[20]	train-rmse:0.350121	valid-rmse:0.397428
[30]	train-rmse:0.337243	valid-rmse:0.385632
[39]	train-rmse:0.333429	valid-rmse:0.382714
Iteration No: 339 ended. Search finished for the next optimal point.
Time taken: 25.4630
Function value obtained: 0.3827
Current minimum: 0.3802
Iteration No: 340 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 12, 'eta': 0.1092912866438762, 'colsample_bytree': 0.41593113849936919, 'max_depth': 63, 'subsample': 0.97508186027892751, 'lambda': 77.898798480200142, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.35075	valid-rmse:5.36885
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.74254	valid-rmse:1.76475
[20]	train-rmse:0.670313	valid-rmse:0.704515
[30]	train-rmse:0.40953	valid-rmse:0.454585
[39]	train-rmse:0.357877	valid-rmse:0.406808
Iteration No: 340 ended. Search finished for the next optimal point.
Time taken: 13.8835
Function value obtained: 0.4068
Current minimum: 0.3802
Iteration No: 341 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 31, 'eta': 0.14246719620449888, 'colsample_bytree': 0.92204921521053995, 'max_depth': 104, 'subsample': 0.99716257761103777, 'lambda': 1.1455924189336966, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.15037	valid-rmse:5.16812
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.16685	valid-rmse:1.19145
[20]	train-rmse:0.416826	valid-rmse:0.464877
[30]	train-rmse:0.331523	valid-rmse:0.389368
[39]	train-rmse:0.323035	valid-rmse:0.383956
Iteration No: 341 ended. Search finished for the next optimal point.
Time taken: 34.3621
Function value obtained: 0.3840
Current minimum: 0.3802
Iteration No: 342 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 86, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21883	valid-rmse:4.2372
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395799	valid-rmse:0.440293
[20]	train-rmse:0.344577	valid-rmse:0.391066
[30]	train-rmse:0.336463	valid-rmse:0.384766
[39]	train-rmse:0.333151	valid-rmse:0.382692
Iteration No: 342 ended. Search finished for the next optimal point.
Time taken: 24.3048
Function value obtained: 0.3827
Current minimum: 0.3802
Iteration No: 343 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 151, 'eta': 0.19371515690746843, 'colsample_bytree': 0.73872362466896302, 'max_depth': 63, 'subsample': 1.0, 'lambda': 34.603102743074416, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84779	valid-rmse:4.86592
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.689734	valid-rmse:0.722595
[20]	train-rmse:0.357779	valid-rmse:0.404368
[30]	train-rmse:0.336636	valid-rmse:0.385105
[39]	train-rmse:0.330685	valid-rmse:0.380937
Iteration No: 343 ended. Search finished for the next optimal point.
Time taken: 20.4454
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 344 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 119, 'eta': 0.29999999999999999, 'colsample_bytree': 0.75352139324599554, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21921	valid-rmse:4.23757
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391653	valid-rmse:0.436952
[20]	train-rmse:0.340052	valid-rmse:0.388832
[30]	train-rmse:0.331679	valid-rmse:0.383224
[39]	train-rmse:0.328252	valid-rmse:0.381947
Iteration No: 344 ended. Search finished for the next optimal point.
Time taken: 24.3726
Function value obtained: 0.3819
Current minimum: 0.3802
Iteration No: 345 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 115, 'eta': 0.21541169361409296, 'colsample_bytree': 1.0, 'max_depth': 71, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.72049	valid-rmse:4.73867
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.579484	valid-rmse:0.615959
[20]	train-rmse:0.353843	valid-rmse:0.400862
[30]	train-rmse:0.33656	valid-rmse:0.385938
[39]	train-rmse:0.330927	valid-rmse:0.382086
Iteration No: 345 ended. Search finished for the next optimal point.
Time taken: 23.4484
Function value obtained: 0.3821
Current minimum: 0.3802
Iteration No: 346 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26037950141630567, 'colsample_bytree': 0.84067328393277729, 'max_depth': 200, 'subsample': 1.0, 'lambda': 39.074257486335981, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.45159	valid-rmse:4.46993
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.438519	valid-rmse:0.48091
[20]	train-rmse:0.34496	valid-rmse:0.391506
[30]	train-rmse:0.336142	valid-rmse:0.384224
[39]	train-rmse:0.332628	valid-rmse:0.381956
Iteration No: 346 ended. Search finished for the next optimal point.
Time taken: 24.4814
Function value obtained: 0.3820
Current minimum: 0.3802
Iteration No: 347 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 163, 'eta': 0.21280168232691254, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 58.527487612944704, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.73494	valid-rmse:4.75318
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.586698	valid-rmse:0.622751
[20]	train-rmse:0.351853	valid-rmse:0.39844
[30]	train-rmse:0.33596	valid-rmse:0.384383
[39]	train-rmse:0.330566	valid-rmse:0.380755
Iteration No: 347 ended. Search finished for the next optimal point.
Time taken: 24.0333
Function value obtained: 0.3808
Current minimum: 0.3802
Iteration No: 348 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26354791571244784, 'colsample_bytree': 1.0, 'max_depth': 82, 'subsample': 1.0, 'lambda': 61.343700764843831, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.43388	valid-rmse:4.45216
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.435739	valid-rmse:0.478041
[20]	train-rmse:0.346174	valid-rmse:0.392504
[30]	train-rmse:0.336952	valid-rmse:0.385013
[39]	train-rmse:0.333124	valid-rmse:0.382352
Iteration No: 348 ended. Search finished for the next optimal point.
Time taken: 23.6217
Function value obtained: 0.3824
Current minimum: 0.3802
Iteration No: 349 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 18, 'eta': 0.25698655668767401, 'colsample_bytree': 0.45000875159165143, 'max_depth': 129, 'subsample': 0.80546818126680919, 'lambda': 55.603688986991521, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.47357	valid-rmse:4.49197
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.450742	valid-rmse:0.492996
[20]	train-rmse:0.34292	valid-rmse:0.393326
[30]	train-rmse:0.330071	valid-rmse:0.384952
[39]	train-rmse:0.325402	valid-rmse:0.383332
Iteration No: 349 ended. Search finished for the next optimal point.
Time taken: 20.1297
Function value obtained: 0.3833
Current minimum: 0.3802
Iteration No: 350 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 81, 'eta': 0.22880941072932592, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.64098	valid-rmse:4.65918
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.525716	valid-rmse:0.564807
[20]	train-rmse:0.348623	valid-rmse:0.397193
[30]	train-rmse:0.334818	valid-rmse:0.385757
[39]	train-rmse:0.329309	valid-rmse:0.382645
Iteration No: 350 ended. Search finished for the next optimal point.
Time taken: 25.7787
Function value obtained: 0.3826
Current minimum: 0.3802
Iteration No: 351 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 142, 'eta': 0.19098192548932696, 'colsample_bytree': 0.82649545172878602, 'max_depth': 200, 'subsample': 1.0, 'lambda': 40.219170287285976, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86403	valid-rmse:4.88223
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.708198	valid-rmse:0.740614
[20]	train-rmse:0.360269	valid-rmse:0.4068
[30]	train-rmse:0.337023	valid-rmse:0.385579
[39]	train-rmse:0.331334	valid-rmse:0.381435
Iteration No: 351 ended. Search finished for the next optimal point.
Time taken: 21.6644
Function value obtained: 0.3814
Current minimum: 0.3802
Iteration No: 352 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 140, 'eta': 0.18805175691351578, 'colsample_bytree': 0.67953833477270553, 'max_depth': 68, 'subsample': 0.80000000000000004, 'lambda': 26.999615961094108, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88138	valid-rmse:4.8994
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.727844	valid-rmse:0.759461
[20]	train-rmse:0.36237	valid-rmse:0.408407
[30]	train-rmse:0.338582	valid-rmse:0.386334
[39]	train-rmse:0.33283	valid-rmse:0.38219
Iteration No: 352 ended. Search finished for the next optimal point.
Time taken: 18.6958
Function value obtained: 0.3822
Current minimum: 0.3802
Iteration No: 353 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 0.40000000000000002, 'max_depth': 85, 'subsample': 1.0, 'lambda': 31.914025484116078, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21643	valid-rmse:4.23469
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.394058	valid-rmse:0.437656
[20]	train-rmse:0.346785	valid-rmse:0.392944
[30]	train-rmse:0.337832	valid-rmse:0.386054
[39]	train-rmse:0.334158	valid-rmse:0.383736
Iteration No: 353 ended. Search finished for the next optimal point.
Time taken: 16.1570
Function value obtained: 0.3837
Current minimum: 0.3802
Iteration No: 354 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 151, 'eta': 0.16669559756508795, 'colsample_bytree': 0.75212731673409672, 'max_depth': 157, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00515	valid-rmse:5.02271
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.881814	valid-rmse:0.909808
[20]	train-rmse:0.36441	valid-rmse:0.412555
[30]	train-rmse:0.333519	valid-rmse:0.384157
[39]	train-rmse:0.329086	valid-rmse:0.380913
Iteration No: 354 ended. Search finished for the next optimal point.
Time taken: 25.9195
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 355 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 143, 'eta': 0.19007918046578212, 'colsample_bytree': 0.82740057554817414, 'max_depth': 200, 'subsample': 1.0, 'lambda': 38.896211178643469, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86935	valid-rmse:4.88755
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.71414	valid-rmse:0.746649
[20]	train-rmse:0.360789	valid-rmse:0.407771
[30]	train-rmse:0.337606	valid-rmse:0.386724
[39]	train-rmse:0.331389	valid-rmse:0.382004
Iteration No: 355 ended. Search finished for the next optimal point.
Time taken: 23.1919
Function value obtained: 0.3820
Current minimum: 0.3802
Iteration No: 356 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26093573314429502, 'colsample_bytree': 0.8508886023641149, 'max_depth': 200, 'subsample': 1.0, 'lambda': 39.686887571970544, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.44831	valid-rmse:4.46665
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.437475	valid-rmse:0.479805
[20]	train-rmse:0.345578	valid-rmse:0.391643
[30]	train-rmse:0.336494	valid-rmse:0.384282
[39]	train-rmse:0.332937	valid-rmse:0.382015
Iteration No: 356 ended. Search finished for the next optimal point.
Time taken: 23.4204
Function value obtained: 0.3820
Current minimum: 0.3802
Iteration No: 357 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 124, 'eta': 0.17874395923522621, 'colsample_bytree': 0.83627874717252049, 'max_depth': 168, 'subsample': 1.0, 'lambda': 30.511815342811289, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93638	valid-rmse:4.95437
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.796687	valid-rmse:0.827189
[20]	train-rmse:0.36749	valid-rmse:0.414065
[30]	train-rmse:0.337333	valid-rmse:0.386516
[39]	train-rmse:0.330965	valid-rmse:0.381728
Iteration No: 357 ended. Search finished for the next optimal point.
Time taken: 23.0512
Function value obtained: 0.3817
Current minimum: 0.3802
Iteration No: 358 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 132, 'eta': 0.26294929598134986, 'colsample_bytree': 0.81996051452709517, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.43845	valid-rmse:4.45672
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.43839	valid-rmse:0.480792
[20]	train-rmse:0.344809	valid-rmse:0.391971
[30]	train-rmse:0.333782	valid-rmse:0.383123
[39]	train-rmse:0.32943	valid-rmse:0.380824
Iteration No: 358 ended. Search finished for the next optimal point.
Time taken: 24.4415
Function value obtained: 0.3808
Current minimum: 0.3802
Iteration No: 359 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 132, 'eta': 0.26253440691279117, 'colsample_bytree': 0.82064993643673279, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.44091	valid-rmse:4.45918
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.439071	valid-rmse:0.481438
[20]	train-rmse:0.344298	valid-rmse:0.391592
[30]	train-rmse:0.333425	valid-rmse:0.382941
[39]	train-rmse:0.329404	valid-rmse:0.380888
Iteration No: 359 ended. Search finished for the next optimal point.
Time taken: 23.4601
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 360 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 151, 'eta': 0.16628311545936045, 'colsample_bytree': 0.74044092075366597, 'max_depth': 154, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.0076	valid-rmse:5.02517
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.885998	valid-rmse:0.913778
[20]	train-rmse:0.364985	valid-rmse:0.412975
[30]	train-rmse:0.333732	valid-rmse:0.38418
[39]	train-rmse:0.329039	valid-rmse:0.380902
Iteration No: 360 ended. Search finished for the next optimal point.
Time taken: 25.6855
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 361 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 29, 'eta': 0.21364098197476841, 'colsample_bytree': 0.40899257378885706, 'max_depth': 65, 'subsample': 0.8338999040436853, 'lambda': 3.9271698252610312, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.72715	valid-rmse:4.74485
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.568286	valid-rmse:0.60566
[20]	train-rmse:0.339366	valid-rmse:0.393872
[30]	train-rmse:0.327865	valid-rmse:0.38677
[39]	train-rmse:0.325145	valid-rmse:0.386803
Iteration No: 361 ended. Search finished for the next optimal point.
Time taken: 22.9009
Function value obtained: 0.3868
Current minimum: 0.3802
Iteration No: 362 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 298, 'eta': 0.23338481750275722, 'colsample_bytree': 0.99527492066038781, 'max_depth': 42, 'subsample': 0.80318067509822, 'lambda': 0.58353800448251891, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.60822	valid-rmse:4.62589
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.482585	valid-rmse:0.522158
[20]	train-rmse:0.343275	valid-rmse:0.390253
[30]	train-rmse:0.336684	valid-rmse:0.384606
[39]	train-rmse:0.334437	valid-rmse:0.38315
Iteration No: 362 ended. Search finished for the next optimal point.
Time taken: 25.7122
Function value obtained: 0.3831
Current minimum: 0.3802
Iteration No: 363 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.21982453586287526, 'colsample_bytree': 1.0, 'max_depth': 72, 'subsample': 1.0, 'lambda': 39.57098318235645, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.69256	valid-rmse:4.71081
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.554302	valid-rmse:0.591408
[20]	train-rmse:0.351641	valid-rmse:0.397436
[30]	train-rmse:0.339007	valid-rmse:0.385973
[39]	train-rmse:0.334553	valid-rmse:0.382512
Iteration No: 363 ended. Search finished for the next optimal point.
Time taken: 24.2621
Function value obtained: 0.3825
Current minimum: 0.3802
Iteration No: 364 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29550679934069757, 'colsample_bytree': 0.99268213765639313, 'max_depth': 91, 'subsample': 0.87279555390277619, 'lambda': 4.6808640294439643, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.23943	valid-rmse:4.25733
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.381895	valid-rmse:0.426097
[20]	train-rmse:0.344455	valid-rmse:0.390021
[30]	train-rmse:0.34058	valid-rmse:0.386834
[39]	train-rmse:0.338378	valid-rmse:0.384969
Iteration No: 364 ended. Search finished for the next optimal point.
Time taken: 24.3233
Function value obtained: 0.3850
Current minimum: 0.3802
Iteration No: 365 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 185, 'eta': 0.21869069010042086, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 57.126126049976925, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.69991	valid-rmse:4.71816
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.561101	valid-rmse:0.597665
[20]	train-rmse:0.351096	valid-rmse:0.39726
[30]	train-rmse:0.336725	valid-rmse:0.384833
[39]	train-rmse:0.331594	valid-rmse:0.38151
Iteration No: 365 ended. Search finished for the next optimal point.
Time taken: 24.6431
Function value obtained: 0.3815
Current minimum: 0.3802
Iteration No: 366 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26767398844495094, 'colsample_bytree': 1.0, 'max_depth': 84, 'subsample': 1.0, 'lambda': 57.863259526707395, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.40907	valid-rmse:4.42742
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.426991	valid-rmse:0.469621
[20]	train-rmse:0.345443	valid-rmse:0.391725
[30]	train-rmse:0.336966	valid-rmse:0.384749
[39]	train-rmse:0.333422	valid-rmse:0.382447
Iteration No: 366 ended. Search finished for the next optimal point.
Time taken: 25.7309
Function value obtained: 0.3824
Current minimum: 0.3802
Iteration No: 367 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 152, 'eta': 0.16608182255172685, 'colsample_bytree': 0.75089702982480333, 'max_depth': 157, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00881	valid-rmse:5.02637
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.887817	valid-rmse:0.915691
[20]	train-rmse:0.364722	valid-rmse:0.41305
[30]	train-rmse:0.333253	valid-rmse:0.384179
[39]	train-rmse:0.329047	valid-rmse:0.381022
Iteration No: 367 ended. Search finished for the next optimal point.
Time taken: 25.5998
Function value obtained: 0.3810
Current minimum: 0.3802
Iteration No: 368 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.19040117766167669, 'colsample_bytree': 0.75593582329731945, 'max_depth': 66, 'subsample': 1.0, 'lambda': 35.142276777384431, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8675	valid-rmse:4.88562
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.711308	valid-rmse:0.743626
[20]	train-rmse:0.360324	valid-rmse:0.406953
[30]	train-rmse:0.337202	valid-rmse:0.385734
[39]	train-rmse:0.330987	valid-rmse:0.381085
Iteration No: 368 ended. Search finished for the next optimal point.
Time taken: 21.3771
Function value obtained: 0.3811
Current minimum: 0.3802
Iteration No: 369 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 128, 'eta': 0.17819492755643929, 'colsample_bytree': 0.83719613654151703, 'max_depth': 170, 'subsample': 1.0, 'lambda': 29.371638393342764, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9396	valid-rmse:4.95759
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.801938	valid-rmse:0.832263
[20]	train-rmse:0.368164	valid-rmse:0.414873
[30]	train-rmse:0.337184	valid-rmse:0.386383
[39]	train-rmse:0.330785	valid-rmse:0.381869
Iteration No: 369 ended. Search finished for the next optimal point.
Time taken: 23.5949
Function value obtained: 0.3819
Current minimum: 0.3802
Iteration No: 370 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.19961042749660746, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.80869	valid-rmse:4.82619
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.629682	valid-rmse:0.663521
[20]	train-rmse:0.346803	valid-rmse:0.394275
[30]	train-rmse:0.335744	valid-rmse:0.384036
[39]	train-rmse:0.333081	valid-rmse:0.382394
Iteration No: 370 ended. Search finished for the next optimal point.
Time taken: 29.2625
Function value obtained: 0.3824
Current minimum: 0.3802
Iteration No: 371 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 283, 'eta': 0.23131595190018558, 'colsample_bytree': 0.40790232003883031, 'max_depth': 199, 'subsample': 0.80032967110450004, 'lambda': 3.0035590141936166, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.62184	valid-rmse:4.6396
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.50036	valid-rmse:0.538849
[20]	train-rmse:0.348131	valid-rmse:0.393848
[30]	train-rmse:0.338853	valid-rmse:0.385676
[39]	train-rmse:0.335362	valid-rmse:0.383341
Iteration No: 371 ended. Search finished for the next optimal point.
Time taken: 18.9987
Function value obtained: 0.3833
Current minimum: 0.3802
Iteration No: 372 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.25219870534630462, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.50222	valid-rmse:4.52046
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.459274	valid-rmse:0.500834
[20]	train-rmse:0.345642	valid-rmse:0.393505
[30]	train-rmse:0.33459	valid-rmse:0.384608
[39]	train-rmse:0.330079	valid-rmse:0.381822
Iteration No: 372 ended. Search finished for the next optimal point.
Time taken: 27.1622
Function value obtained: 0.3818
Current minimum: 0.3802
Iteration No: 373 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 161, 'eta': 0.20200974574771663, 'colsample_bytree': 1.0, 'max_depth': 71, 'subsample': 1.0, 'lambda': 61.697250089513204, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.79927	valid-rmse:4.81745
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.643463	valid-rmse:0.677745
[20]	train-rmse:0.355972	valid-rmse:0.402379
[30]	train-rmse:0.337355	valid-rmse:0.38567
[39]	train-rmse:0.331673	valid-rmse:0.381523
Iteration No: 373 ended. Search finished for the next optimal point.
Time taken: 23.9665
Function value obtained: 0.3815
Current minimum: 0.3802
Iteration No: 374 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 151, 'eta': 0.18622230113455554, 'colsample_bytree': 0.70327751455414322, 'max_depth': 70, 'subsample': 0.80000000000000004, 'lambda': 27.270661593067402, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89227	valid-rmse:4.91029
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.740808	valid-rmse:0.772111
[20]	train-rmse:0.363278	valid-rmse:0.40932
[30]	train-rmse:0.339056	valid-rmse:0.386677
[39]	train-rmse:0.333692	valid-rmse:0.382624
Iteration No: 374 ended. Search finished for the next optimal point.
Time taken: 20.6615
Function value obtained: 0.3826
Current minimum: 0.3802
Iteration No: 375 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 178, 'eta': 0.26158103376313968, 'colsample_bytree': 1.0, 'max_depth': 89, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4466	valid-rmse:4.46493
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.440669	valid-rmse:0.482927
[20]	train-rmse:0.345279	valid-rmse:0.392385
[30]	train-rmse:0.335257	valid-rmse:0.384199
[39]	train-rmse:0.33093	valid-rmse:0.381403
Iteration No: 375 ended. Search finished for the next optimal point.
Time taken: 25.7439
Function value obtained: 0.3814
Current minimum: 0.3802
Iteration No: 376 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 143, 'eta': 0.16539183350866371, 'colsample_bytree': 0.64986266623611944, 'max_depth': 123, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01356	valid-rmse:5.0312
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.895181	valid-rmse:0.92289
[20]	train-rmse:0.366163	valid-rmse:0.414041
[30]	train-rmse:0.333303	valid-rmse:0.383844
[39]	train-rmse:0.32902	valid-rmse:0.380643
Iteration No: 376 ended. Search finished for the next optimal point.
Time taken: 23.7651
Function value obtained: 0.3806
Current minimum: 0.3802
Iteration No: 377 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 150, 'eta': 0.16564594563075191, 'colsample_bytree': 0.73094339436414213, 'max_depth': 153, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01142	valid-rmse:5.02897
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.891972	valid-rmse:0.919755
[20]	train-rmse:0.365528	valid-rmse:0.413735
[30]	train-rmse:0.333196	valid-rmse:0.384046
[39]	train-rmse:0.328744	valid-rmse:0.380937
Iteration No: 377 ended. Search finished for the next optimal point.
Time taken: 27.1566
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 378 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 175, 'eta': 0.21926671047603263, 'colsample_bytree': 0.82066724033260918, 'max_depth': 200, 'subsample': 1.0, 'lambda': 58.363169371171054, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.69653	valid-rmse:4.71479
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.559146	valid-rmse:0.5962
[20]	train-rmse:0.350942	valid-rmse:0.397519
[30]	train-rmse:0.336275	valid-rmse:0.384437
[39]	train-rmse:0.331649	valid-rmse:0.381367
Iteration No: 378 ended. Search finished for the next optimal point.
Time taken: 23.1381
Function value obtained: 0.3814
Current minimum: 0.3802
Iteration No: 379 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 24, 'eta': 0.29318513371972366, 'colsample_bytree': 0.97647294293502962, 'max_depth': 66, 'subsample': 0.83797149267310811, 'lambda': 88.366152720332138, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.25963	valid-rmse:4.27798
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395362	valid-rmse:0.44108
[20]	train-rmse:0.339076	valid-rmse:0.390533
[30]	train-rmse:0.330088	valid-rmse:0.385257
[39]	train-rmse:0.326699	valid-rmse:0.384566
Iteration No: 379 ended. Search finished for the next optimal point.
Time taken: 33.6905
Function value obtained: 0.3846
Current minimum: 0.3802
Iteration No: 380 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 12, 'eta': 0.29894971061048559, 'colsample_bytree': 0.94185283675896603, 'max_depth': 196, 'subsample': 0.82132069343875935, 'lambda': 89.06896959804061, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2256	valid-rmse:4.24396
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.392345	valid-rmse:0.437587
[20]	train-rmse:0.343672	valid-rmse:0.39148
[30]	train-rmse:0.337006	valid-rmse:0.386655
[39]	train-rmse:0.333868	valid-rmse:0.384691
Iteration No: 380 ended. Search finished for the next optimal point.
Time taken: 32.0925
Function value obtained: 0.3847
Current minimum: 0.3802
Iteration No: 381 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 143, 'eta': 0.16636966868671674, 'colsample_bytree': 0.62840155615475601, 'max_depth': 113, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00772	valid-rmse:5.02536
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.88543	valid-rmse:0.913358
[20]	train-rmse:0.364602	valid-rmse:0.412666
[30]	train-rmse:0.332999	valid-rmse:0.383731
[39]	train-rmse:0.328824	valid-rmse:0.380513
Iteration No: 381 ended. Search finished for the next optimal point.
Time taken: 25.0842
Function value obtained: 0.3805
Current minimum: 0.3802
Iteration No: 382 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 142, 'eta': 0.16647991092852216, 'colsample_bytree': 0.62606368105677335, 'max_depth': 112, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00644	valid-rmse:5.024
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.88403	valid-rmse:0.912158
[20]	train-rmse:0.363837	valid-rmse:0.412624
[30]	train-rmse:0.332331	valid-rmse:0.383782
[39]	train-rmse:0.328243	valid-rmse:0.380899
Iteration No: 382 ended. Search finished for the next optimal point.
Time taken: 24.5086
Function value obtained: 0.3809
Current minimum: 0.3802
Iteration No: 383 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 181, 'eta': 0.26772393576102615, 'colsample_bytree': 1.0, 'max_depth': 90, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41017	valid-rmse:4.42851
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.429389	valid-rmse:0.472365
[20]	train-rmse:0.344595	valid-rmse:0.391752
[30]	train-rmse:0.334948	valid-rmse:0.384139
[39]	train-rmse:0.330993	valid-rmse:0.381728
Iteration No: 383 ended. Search finished for the next optimal point.
Time taken: 27.8732
Function value obtained: 0.3817
Current minimum: 0.3802
Iteration No: 384 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 154, 'eta': 0.1661961802048027, 'colsample_bytree': 0.75191778723668712, 'max_depth': 157, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00813	valid-rmse:5.02569
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.886626	valid-rmse:0.914577
[20]	train-rmse:0.364972	valid-rmse:0.413342
[30]	train-rmse:0.333598	valid-rmse:0.384321
[39]	train-rmse:0.329296	valid-rmse:0.381293
Iteration No: 384 ended. Search finished for the next optimal point.
Time taken: 27.7159
Function value obtained: 0.3813
Current minimum: 0.3802
Iteration No: 385 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 104, 'eta': 0.2134833732232225, 'colsample_bytree': 1.0, 'max_depth': 72, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.73194	valid-rmse:4.75011
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.588766	valid-rmse:0.625361
[20]	train-rmse:0.353539	valid-rmse:0.401387
[30]	train-rmse:0.336111	valid-rmse:0.386343
[39]	train-rmse:0.330386	valid-rmse:0.382316
Iteration No: 385 ended. Search finished for the next optimal point.
Time taken: 26.1479
Function value obtained: 0.3823
Current minimum: 0.3802
Iteration No: 386 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.23847806577553826, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 34.156403430679916, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.58149	valid-rmse:4.59978
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.485979	valid-rmse:0.525818
[20]	train-rmse:0.346431	valid-rmse:0.392711
[30]	train-rmse:0.336841	valid-rmse:0.384372
[39]	train-rmse:0.332626	valid-rmse:0.381309
Iteration No: 386 ended. Search finished for the next optimal point.
Time taken: 28.3924
Function value obtained: 0.3813
Current minimum: 0.3802
Iteration No: 387 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.20022856453772098, 'colsample_bytree': 0.79933903040639598, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.80895	valid-rmse:4.82637
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.628781	valid-rmse:0.662483
[20]	train-rmse:0.350529	valid-rmse:0.397358
[30]	train-rmse:0.339334	valid-rmse:0.387333
[39]	train-rmse:0.336076	valid-rmse:0.384944
Iteration No: 387 ended. Search finished for the next optimal point.
Time taken: 26.3910
Function value obtained: 0.3849
Current minimum: 0.3802
Iteration No: 388 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 107, 'eta': 0.23074912090264563, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.62947	valid-rmse:4.64768
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.518794	valid-rmse:0.558093
[20]	train-rmse:0.347933	valid-rmse:0.395885
[30]	train-rmse:0.334625	valid-rmse:0.38467
[39]	train-rmse:0.329773	valid-rmse:0.38198
Iteration No: 388 ended. Search finished for the next optimal point.
Time taken: 27.8903
Function value obtained: 0.3820
Current minimum: 0.3802
Iteration No: 389 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 152, 'eta': 0.29999999999999999, 'colsample_bytree': 0.72807137815074618, 'max_depth': 105, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21908	valid-rmse:4.23747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.39277	valid-rmse:0.437453
[20]	train-rmse:0.342148	valid-rmse:0.38986
[30]	train-rmse:0.332601	valid-rmse:0.382554
[39]	train-rmse:0.329308	valid-rmse:0.381279
Iteration No: 389 ended. Search finished for the next optimal point.
Time taken: 24.9671
Function value obtained: 0.3813
Current minimum: 0.3802
Iteration No: 390 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 139, 'eta': 0.16780756483772866, 'colsample_bytree': 0.59391311926474044, 'max_depth': 103, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99856	valid-rmse:5.01615
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.871455	valid-rmse:0.899751
[20]	train-rmse:0.362322	valid-rmse:0.410631
[30]	train-rmse:0.332139	valid-rmse:0.383233
[39]	train-rmse:0.327921	valid-rmse:0.380148
Iteration No: 390 ended. Search finished for the next optimal point.
Time taken: 25.0728
Function value obtained: 0.3801
Current minimum: 0.3801
Iteration No: 391 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.1679028798415664, 'colsample_bytree': 0.59548288139068761, 'max_depth': 102, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99864	valid-rmse:5.01623
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.87085	valid-rmse:0.8992
[20]	train-rmse:0.362836	valid-rmse:0.411565
[30]	train-rmse:0.332885	valid-rmse:0.384162
[39]	train-rmse:0.328677	valid-rmse:0.381033
Iteration No: 391 ended. Search finished for the next optimal point.
Time taken: 25.3393
Function value obtained: 0.3810
Current minimum: 0.3801
Iteration No: 392 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 141, 'eta': 0.1659178437782807, 'colsample_bytree': 0.62152491521350206, 'max_depth': 115, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00983	valid-rmse:5.02742
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.88983	valid-rmse:0.917776
[20]	train-rmse:0.36495	valid-rmse:0.413164
[30]	train-rmse:0.332699	valid-rmse:0.383597
[39]	train-rmse:0.328265	valid-rmse:0.380294
Iteration No: 392 ended. Search finished for the next optimal point.
Time taken: 25.2186
Function value obtained: 0.3803
Current minimum: 0.3801
Iteration No: 393 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.16860491657216023, 'colsample_bytree': 0.58288967041044881, 'max_depth': 99, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99386	valid-rmse:5.01138
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.863571	valid-rmse:0.892072
[20]	train-rmse:0.361699	valid-rmse:0.410448
[30]	train-rmse:0.332626	valid-rmse:0.38394
[39]	train-rmse:0.32844	valid-rmse:0.38092
Iteration No: 393 ended. Search finished for the next optimal point.
Time taken: 24.4352
Function value obtained: 0.3809
Current minimum: 0.3801
Iteration No: 394 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 107, 'eta': 0.17088254897104152, 'colsample_bytree': 0.40000000000000002, 'max_depth': 88, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98053	valid-rmse:4.99808
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.845914	valid-rmse:0.874922
[20]	train-rmse:0.362963	valid-rmse:0.411933
[30]	train-rmse:0.334055	valid-rmse:0.385889
[39]	train-rmse:0.328847	valid-rmse:0.382279
Iteration No: 394 ended. Search finished for the next optimal point.
Time taken: 21.0430
Function value obtained: 0.3823
Current minimum: 0.3801
Iteration No: 395 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 131, 'eta': 0.17530451183063647, 'colsample_bytree': 1.0, 'max_depth': 168, 'subsample': 1.0, 'lambda': 31.366773607853393, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95688	valid-rmse:4.97487
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.825529	valid-rmse:0.855412
[20]	train-rmse:0.371179	valid-rmse:0.417523
[30]	train-rmse:0.337818	valid-rmse:0.386802
[39]	train-rmse:0.330945	valid-rmse:0.381493
Iteration No: 395 ended. Search finished for the next optimal point.
Time taken: 26.6888
Function value obtained: 0.3815
Current minimum: 0.3801
Iteration No: 396 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 126, 'eta': 0.17169120121463213, 'colsample_bytree': 0.72075894144456121, 'max_depth': 99, 'subsample': 1.0, 'lambda': 22.780649453352634, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97825	valid-rmse:4.99617
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.855533	valid-rmse:0.884597
[20]	train-rmse:0.373517	valid-rmse:0.419528
[30]	train-rmse:0.337699	valid-rmse:0.386472
[39]	train-rmse:0.330525	valid-rmse:0.380951
Iteration No: 396 ended. Search finished for the next optimal point.
Time taken: 22.7556
Function value obtained: 0.3810
Current minimum: 0.3801
Iteration No: 397 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 151, 'eta': 0.26597452226306911, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.42051	valid-rmse:4.4388
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.432852	valid-rmse:0.475518
[20]	train-rmse:0.344137	valid-rmse:0.391593
[30]	train-rmse:0.334865	valid-rmse:0.384708
[39]	train-rmse:0.330382	valid-rmse:0.382107
Iteration No: 397 ended. Search finished for the next optimal point.
Time taken: 28.8023
Function value obtained: 0.3821
Current minimum: 0.3801
Iteration No: 398 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 92, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21883	valid-rmse:4.2372
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.395799	valid-rmse:0.440293
[20]	train-rmse:0.344577	valid-rmse:0.391066
[30]	train-rmse:0.336463	valid-rmse:0.384766
[39]	train-rmse:0.333151	valid-rmse:0.382692
Iteration No: 398 ended. Search finished for the next optimal point.
Time taken: 27.4663
Function value obtained: 0.3827
Current minimum: 0.3801
Iteration No: 399 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 145, 'eta': 0.16419675118386787, 'colsample_bytree': 0.70622718819269859, 'max_depth': 142, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02007	valid-rmse:5.03764
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.906704	valid-rmse:0.934303
[20]	train-rmse:0.367375	valid-rmse:0.415536
[30]	train-rmse:0.333164	valid-rmse:0.38407
[39]	train-rmse:0.328643	valid-rmse:0.380806
Iteration No: 399 ended. Search finished for the next optimal point.
Time taken: 26.8765
Function value obtained: 0.3808
Current minimum: 0.3801
Iteration No: 400 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 145, 'eta': 0.16423133126449746, 'colsample_bytree': 0.70459268106623085, 'max_depth': 141, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01986	valid-rmse:5.03743
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.906402	valid-rmse:0.933912
[20]	train-rmse:0.367142	valid-rmse:0.415021
[30]	train-rmse:0.333327	valid-rmse:0.383854
[39]	train-rmse:0.328806	valid-rmse:0.380382
Iteration No: 400 ended. Search finished for the next optimal point.
Time taken: 26.8362
Function value obtained: 0.3804
Current minimum: 0.3801
Iteration No: 401 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 125, 'eta': 0.1711546996629762, 'colsample_bytree': 0.72059869536987775, 'max_depth': 102, 'subsample': 1.0, 'lambda': 22.085514291822726, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98141	valid-rmse:4.99933
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.860094	valid-rmse:0.889051
[20]	train-rmse:0.37439	valid-rmse:0.420281
[30]	train-rmse:0.337612	valid-rmse:0.386695
[39]	train-rmse:0.330299	valid-rmse:0.381154
Iteration No: 401 ended. Search finished for the next optimal point.
Time taken: 24.1736
Function value obtained: 0.3812
Current minimum: 0.3801
Iteration No: 402 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 146, 'eta': 0.16426719026384484, 'colsample_bytree': 0.71555838494192647, 'max_depth': 145, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01965	valid-rmse:5.03721
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.906333	valid-rmse:0.933894
[20]	train-rmse:0.36725	valid-rmse:0.415441
[30]	train-rmse:0.333278	valid-rmse:0.384124
[39]	train-rmse:0.328916	valid-rmse:0.380665
Iteration No: 402 ended. Search finished for the next optimal point.
Time taken: 26.9162
Function value obtained: 0.3807
Current minimum: 0.3801
Iteration No: 403 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 154, 'eta': 0.16574405923124921, 'colsample_bytree': 0.69954296662279769, 'max_depth': 137, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01134	valid-rmse:5.02885
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.891777	valid-rmse:0.91942
[20]	train-rmse:0.367067	valid-rmse:0.414486
[30]	train-rmse:0.334987	valid-rmse:0.384673
[39]	train-rmse:0.330598	valid-rmse:0.381325
Iteration No: 403 ended. Search finished for the next optimal point.
Time taken: 25.7706
Function value obtained: 0.3813
Current minimum: 0.3801
Iteration No: 404 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 136, 'eta': 0.18180970259596238, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 31.332384254589481, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91819	valid-rmse:4.93617
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.772401	valid-rmse:0.803433
[20]	train-rmse:0.364527	valid-rmse:0.411652
[30]	train-rmse:0.336844	valid-rmse:0.385911
[39]	train-rmse:0.330667	valid-rmse:0.381539
Iteration No: 404 ended. Search finished for the next optimal point.
Time taken: 27.4365
Function value obtained: 0.3815
Current minimum: 0.3801
Iteration No: 405 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 126, 'eta': 0.17110752952694158, 'colsample_bytree': 0.7189368021647059, 'max_depth': 103, 'subsample': 1.0, 'lambda': 21.553984504294682, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98167	valid-rmse:4.99959
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.86049	valid-rmse:0.889459
[20]	train-rmse:0.37402	valid-rmse:0.419958
[30]	train-rmse:0.337649	valid-rmse:0.386447
[39]	train-rmse:0.331114	valid-rmse:0.381326
Iteration No: 405 ended. Search finished for the next optimal point.
Time taken: 24.3879
Function value obtained: 0.3813
Current minimum: 0.3801
Iteration No: 406 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 260, 'eta': 0.16513893708749836, 'colsample_bytree': 0.98572648800737617, 'max_depth': 197, 'subsample': 0.80379383634721058, 'lambda': 88.221535137524327, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01935	valid-rmse:5.03747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.931035	valid-rmse:0.959483
[20]	train-rmse:0.39959	valid-rmse:0.443742
[30]	train-rmse:0.351502	valid-rmse:0.397078
[39]	train-rmse:0.341663	valid-rmse:0.387875
Iteration No: 406 ended. Search finished for the next optimal point.
Time taken: 22.9133
Function value obtained: 0.3879
Current minimum: 0.3801
Iteration No: 407 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 284, 'eta': 0.15620811884104668, 'colsample_bytree': 0.41165330741166622, 'max_depth': 153, 'subsample': 0.94502421558158256, 'lambda': 2.536979792341064, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.06905	valid-rmse:5.08688
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.0056	valid-rmse:1.03202
[20]	train-rmse:0.395654	valid-rmse:0.440183
[30]	train-rmse:0.344388	valid-rmse:0.391686
[39]	train-rmse:0.337627	valid-rmse:0.385489
Iteration No: 407 ended. Search finished for the next optimal point.
Time taken: 20.9488
Function value obtained: 0.3855
Current minimum: 0.3801
Iteration No: 408 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.27558788284791524, 'colsample_bytree': 0.42739087645636903, 'max_depth': 59, 'subsample': 0.98479984383227481, 'lambda': 3.2191403746059599, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.35815	valid-rmse:4.37595
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.403823	valid-rmse:0.447392
[20]	train-rmse:0.343131	valid-rmse:0.389745
[30]	train-rmse:0.336164	valid-rmse:0.384399
[39]	train-rmse:0.332966	valid-rmse:0.382437
Iteration No: 408 ended. Search finished for the next optimal point.
Time taken: 21.8767
Function value obtained: 0.3824
Current minimum: 0.3801
Iteration No: 409 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.267094689246409, 'colsample_bytree': 0.77234787901997159, 'max_depth': 83, 'subsample': 1.0, 'lambda': 38.076626562481529, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41194	valid-rmse:4.43019
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.425211	valid-rmse:0.467843
[20]	train-rmse:0.344645	valid-rmse:0.390628
[30]	train-rmse:0.335931	valid-rmse:0.383439
[39]	train-rmse:0.333046	valid-rmse:0.381841
Iteration No: 409 ended. Search finished for the next optimal point.
Time taken: 26.2171
Function value obtained: 0.3818
Current minimum: 0.3801
Iteration No: 410 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 144, 'eta': 0.16629846010355664, 'colsample_bytree': 0.6496816036782932, 'max_depth': 113, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00753	valid-rmse:5.02509
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.885797	valid-rmse:0.91395
[20]	train-rmse:0.364246	valid-rmse:0.412651
[30]	train-rmse:0.332543	valid-rmse:0.38374
[39]	train-rmse:0.328269	valid-rmse:0.380355
Iteration No: 410 ended. Search finished for the next optimal point.
Time taken: 27.1172
Function value obtained: 0.3804
Current minimum: 0.3801
Iteration No: 411 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 153, 'eta': 0.17181358767279414, 'colsample_bytree': 0.62215733745707413, 'max_depth': 91, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97464	valid-rmse:4.99223
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.833864	valid-rmse:0.86287
[20]	train-rmse:0.358297	valid-rmse:0.406901
[30]	train-rmse:0.332351	valid-rmse:0.383095
[39]	train-rmse:0.328324	valid-rmse:0.380132
Iteration No: 411 ended. Search finished for the next optimal point.
Time taken: 27.1671
Function value obtained: 0.3801
Current minimum: 0.3801
Iteration No: 412 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 145, 'eta': 0.16729734037637933, 'colsample_bytree': 0.63976184352531473, 'max_depth': 107, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00157	valid-rmse:5.01913
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.876171	valid-rmse:0.904436
[20]	train-rmse:0.363094	valid-rmse:0.411571
[30]	train-rmse:0.332699	valid-rmse:0.383736
[39]	train-rmse:0.328534	valid-rmse:0.380989
Iteration No: 412 ended. Search finished for the next optimal point.
Time taken: 26.9305
Function value obtained: 0.3810
Current minimum: 0.3801
Iteration No: 413 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 110, 'eta': 0.26897297085079719, 'colsample_bytree': 0.74743136192359128, 'max_depth': 99, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4031	valid-rmse:4.42139
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.428399	valid-rmse:0.471544
[20]	train-rmse:0.343566	valid-rmse:0.391873
[30]	train-rmse:0.33275	valid-rmse:0.383517
[39]	train-rmse:0.328478	valid-rmse:0.381241
Iteration No: 413 ended. Search finished for the next optimal point.
Time taken: 26.5733
Function value obtained: 0.3812
Current minimum: 0.3801
Iteration No: 414 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 142, 'eta': 0.16396805611142048, 'colsample_bytree': 0.75355042143575379, 'max_depth': 151, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02142	valid-rmse:5.03898
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.908774	valid-rmse:0.936128
[20]	train-rmse:0.367578	valid-rmse:0.415558
[30]	train-rmse:0.333469	valid-rmse:0.384498
[39]	train-rmse:0.329029	valid-rmse:0.381225
Iteration No: 414 ended. Search finished for the next optimal point.
Time taken: 30.3050
Function value obtained: 0.3812
Current minimum: 0.3801
Iteration No: 415 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 296, 'eta': 0.29919697495891351, 'colsample_bytree': 0.43906012442889791, 'max_depth': 171, 'subsample': 0.94788091561517551, 'lambda': 5.8822785171420158, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21825	valid-rmse:4.23616
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.382233	valid-rmse:0.426871
[20]	train-rmse:0.341735	valid-rmse:0.388448
[30]	train-rmse:0.335446	valid-rmse:0.383846
[39]	train-rmse:0.332384	valid-rmse:0.382081
Iteration No: 415 ended. Search finished for the next optimal point.
Time taken: 22.3044
Function value obtained: 0.3821
Current minimum: 0.3801
Iteration No: 416 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 10, 'eta': 0.29999999999999999, 'colsample_bytree': 0.40000000000000002, 'max_depth': 122, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21902	valid-rmse:4.23746
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.400406	valid-rmse:0.446545
[20]	train-rmse:0.341659	valid-rmse:0.394715
[30]	train-rmse:0.328864	valid-rmse:0.386971
[39]	train-rmse:0.323873	valid-rmse:0.385011
Iteration No: 416 ended. Search finished for the next optimal point.
Time taken: 24.7812
Function value obtained: 0.3850
Current minimum: 0.3801
Iteration No: 417 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 144, 'eta': 0.17628328064605325, 'colsample_bytree': 0.66682943365517433, 'max_depth': 87, 'subsample': 0.80000000000000004, 'lambda': 16.52177824581867, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95081	valid-rmse:4.96881
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.81487	valid-rmse:0.844525
[20]	train-rmse:0.368232	valid-rmse:0.414552
[30]	train-rmse:0.338482	valid-rmse:0.386974
[39]	train-rmse:0.332802	valid-rmse:0.382924
Iteration No: 417 ended. Search finished for the next optimal point.
Time taken: 23.8480
Function value obtained: 0.3829
Current minimum: 0.3801
Iteration No: 418 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 167, 'eta': 0.20642307528789117, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 55.856207093568976, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.77274	valid-rmse:4.79097
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.618894	valid-rmse:0.653852
[20]	train-rmse:0.353942	valid-rmse:0.400633
[30]	train-rmse:0.337043	valid-rmse:0.385365
[39]	train-rmse:0.331865	valid-rmse:0.381933
Iteration No: 418 ended. Search finished for the next optimal point.
Time taken: 28.4625
Function value obtained: 0.3819
Current minimum: 0.3801
Iteration No: 419 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.26598356129750178, 'colsample_bytree': 0.82580573651853706, 'max_depth': 95, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.42046	valid-rmse:4.43873
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.433603	valid-rmse:0.476447
[20]	train-rmse:0.34423	valid-rmse:0.392006
[30]	train-rmse:0.333868	valid-rmse:0.38396
[39]	train-rmse:0.329763	valid-rmse:0.381431
Iteration No: 419 ended. Search finished for the next optimal point.
Time taken: 27.0683
Function value obtained: 0.3814
Current minimum: 0.3801
Iteration No: 420 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 28, 'eta': 0.18573447035146873, 'colsample_bytree': 0.42791897079264413, 'max_depth': 55, 'subsample': 0.99804022122747371, 'lambda': 84.430433271563288, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89681	valid-rmse:4.91502
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.757082	valid-rmse:0.788926
[20]	train-rmse:0.377217	valid-rmse:0.422673
[30]	train-rmse:0.347453	valid-rmse:0.394518
[39]	train-rmse:0.341376	valid-rmse:0.38882
Iteration No: 420 ended. Search finished for the next optimal point.
Time taken: 20.0052
Function value obtained: 0.3888
Current minimum: 0.3801
Iteration No: 421 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 143, 'eta': 0.27238787122600994, 'colsample_bytree': 0.77427325627824828, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.38274	valid-rmse:4.40107
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.422055	valid-rmse:0.465371
[20]	train-rmse:0.34336	valid-rmse:0.39091
[30]	train-rmse:0.333427	valid-rmse:0.383343
[39]	train-rmse:0.329662	valid-rmse:0.381279
Iteration No: 421 ended. Search finished for the next optimal point.
Time taken: 25.9948
Function value obtained: 0.3813
Current minimum: 0.3801
Iteration No: 422 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.16414090326798475, 'colsample_bytree': 0.68777662319042299, 'max_depth': 133, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02038	valid-rmse:5.03793
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.90722	valid-rmse:0.934667
[20]	train-rmse:0.367053	valid-rmse:0.415041
[30]	train-rmse:0.332907	valid-rmse:0.383739
[39]	train-rmse:0.328205	valid-rmse:0.380186
Iteration No: 422 ended. Search finished for the next optimal point.
Time taken: 27.6523
Function value obtained: 0.3802
Current minimum: 0.3801
Iteration No: 423 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 137, 'eta': 0.1640660900400947, 'colsample_bytree': 0.68844793384845215, 'max_depth': 134, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02083	valid-rmse:5.03839
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.908119	valid-rmse:0.935856
[20]	train-rmse:0.367238	valid-rmse:0.415689
[30]	train-rmse:0.332922	valid-rmse:0.384198
[39]	train-rmse:0.328569	valid-rmse:0.380873
Iteration No: 423 ended. Search finished for the next optimal point.
Time taken: 28.2365
Function value obtained: 0.3809
Current minimum: 0.3801
Iteration No: 424 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 178, 'eta': 0.26639389296324445, 'colsample_bytree': 1.0, 'max_depth': 94, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41806	valid-rmse:4.4364
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.432701	valid-rmse:0.475562
[20]	train-rmse:0.344867	valid-rmse:0.391966
[30]	train-rmse:0.335323	valid-rmse:0.38449
[39]	train-rmse:0.331299	valid-rmse:0.382216
Iteration No: 424 ended. Search finished for the next optimal point.
Time taken: 29.4318
Function value obtained: 0.3822
Current minimum: 0.3801
Iteration No: 425 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 123, 'eta': 0.17018093826933001, 'colsample_bytree': 0.73365917167291306, 'max_depth': 112, 'subsample': 1.0, 'lambda': 21.521047350972673, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98718	valid-rmse:5.0051
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.869097	valid-rmse:0.897899
[20]	train-rmse:0.374955	valid-rmse:0.420959
[30]	train-rmse:0.337134	valid-rmse:0.386359
[39]	train-rmse:0.330479	valid-rmse:0.381249
Iteration No: 425 ended. Search finished for the next optimal point.
Time taken: 25.4372
Function value obtained: 0.3812
Current minimum: 0.3801
Iteration No: 426 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 148, 'eta': 0.16458331799091719, 'colsample_bytree': 0.78844905527192721, 'max_depth': 158, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01837	valid-rmse:5.036
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.903175	valid-rmse:0.93071
[20]	train-rmse:0.367508	valid-rmse:0.415615
[30]	train-rmse:0.334443	valid-rmse:0.385019
[39]	train-rmse:0.330009	valid-rmse:0.381836
Iteration No: 426 ended. Search finished for the next optimal point.
Time taken: 31.0303
Function value obtained: 0.3818
Current minimum: 0.3801
Iteration No: 427 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 131, 'eta': 0.17324540235853669, 'colsample_bytree': 0.71249922706776314, 'max_depth': 92, 'subsample': 1.0, 'lambda': 21.452113553213756, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96894	valid-rmse:4.98686
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.841777	valid-rmse:0.871086
[20]	train-rmse:0.371166	valid-rmse:0.417443
[30]	train-rmse:0.337106	valid-rmse:0.386172
[39]	train-rmse:0.330379	valid-rmse:0.381111
Iteration No: 427 ended. Search finished for the next optimal point.
Time taken: 24.0335
Function value obtained: 0.3811
Current minimum: 0.3801
Iteration No: 428 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 290, 'eta': 0.29301893711934573, 'colsample_bytree': 0.42989997457249085, 'max_depth': 78, 'subsample': 0.99502305692535287, 'lambda': 88.917540907923168, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.26057	valid-rmse:4.27899
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.407014	valid-rmse:0.4505
[20]	train-rmse:0.352816	valid-rmse:0.397997
[30]	train-rmse:0.343438	valid-rmse:0.389758
[39]	train-rmse:0.34036	valid-rmse:0.387178
Iteration No: 428 ended. Search finished for the next optimal point.
Time taken: 20.0198
Function value obtained: 0.3872
Current minimum: 0.3801
Iteration No: 429 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.16772771302101852, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99896	valid-rmse:5.01658
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.872237	valid-rmse:0.900535
[20]	train-rmse:0.363635	valid-rmse:0.412553
[30]	train-rmse:0.334767	valid-rmse:0.385853
[39]	train-rmse:0.330679	valid-rmse:0.383115
Iteration No: 429 ended. Search finished for the next optimal point.
Time taken: 35.5655
Function value obtained: 0.3831
Current minimum: 0.3801
Iteration No: 430 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 153, 'eta': 0.16740859234577521, 'colsample_bytree': 0.65656407969002806, 'max_depth': 119, 'subsample': 0.80000000000000004, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00142	valid-rmse:5.01892
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.875476	valid-rmse:0.903643
[20]	train-rmse:0.365014	valid-rmse:0.412664
[30]	train-rmse:0.335123	valid-rmse:0.384842
[39]	train-rmse:0.331142	valid-rmse:0.38212
Iteration No: 430 ended. Search finished for the next optimal point.
Time taken: 26.4858
Function value obtained: 0.3821
Current minimum: 0.3801
Iteration No: 431 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 163, 'eta': 0.18622608733850748, 'colsample_bytree': 0.70705203698839858, 'max_depth': 71, 'subsample': 1.0, 'lambda': 21.666391390010407, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89173	valid-rmse:4.90967
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.738042	valid-rmse:0.769528
[20]	train-rmse:0.360336	valid-rmse:0.407037
[30]	train-rmse:0.336296	valid-rmse:0.385231
[39]	train-rmse:0.330751	valid-rmse:0.381235
Iteration No: 431 ended. Search finished for the next optimal point.
Time taken: 24.3622
Function value obtained: 0.3812
Current minimum: 0.3801
Iteration No: 432 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 145, 'eta': 0.18111650745224467, 'colsample_bytree': 0.70507007842959868, 'max_depth': 75, 'subsample': 1.0, 'lambda': 22.983115402235239, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92218	valid-rmse:4.9401
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.776384	valid-rmse:0.806802
[20]	train-rmse:0.363784	valid-rmse:0.41002
[30]	train-rmse:0.336254	valid-rmse:0.385148
[39]	train-rmse:0.330092	valid-rmse:0.380477
Iteration No: 432 ended. Search finished for the next optimal point.
Time taken: 23.9928
Function value obtained: 0.3805
Current minimum: 0.3801
Iteration No: 433 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.27221377073952935, 'colsample_bytree': 0.79140068489900428, 'max_depth': 200, 'subsample': 1.0, 'lambda': 39.781397775808635, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.3816	valid-rmse:4.39991
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.419345	valid-rmse:0.462576
[20]	train-rmse:0.344872	valid-rmse:0.391578
[30]	train-rmse:0.336245	valid-rmse:0.384715
[39]	train-rmse:0.332982	valid-rmse:0.382796
Iteration No: 433 ended. Search finished for the next optimal point.
Time taken: 26.1851
Function value obtained: 0.3828
Current minimum: 0.3801
Iteration No: 434 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.17875152219555401, 'colsample_bytree': 0.62668560016871022, 'max_depth': 80, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93323	valid-rmse:4.95077
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.773963	valid-rmse:0.803995
[20]	train-rmse:0.353025	valid-rmse:0.40138
[30]	train-rmse:0.332757	valid-rmse:0.38288
[39]	train-rmse:0.329223	valid-rmse:0.380744
Iteration No: 434 ended. Search finished for the next optimal point.
Time taken: 27.8834
Function value obtained: 0.3807
Current minimum: 0.3801
Iteration No: 435 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.20790161302546178, 'colsample_bytree': 0.74737180153510874, 'max_depth': 73, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.76337	valid-rmse:4.78076
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.587418	valid-rmse:0.622488
[20]	train-rmse:0.348656	valid-rmse:0.395646
[30]	train-rmse:0.339564	valid-rmse:0.387665
[39]	train-rmse:0.336363	valid-rmse:0.385406
Iteration No: 435 ended. Search finished for the next optimal point.
Time taken: 27.1441
Function value obtained: 0.3854
Current minimum: 0.3801
Iteration No: 436 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 120, 'eta': 0.17024414669143839, 'colsample_bytree': 0.74074616658783587, 'max_depth': 112, 'subsample': 1.0, 'lambda': 23.226730928108587, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98687	valid-rmse:5.00479
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.869114	valid-rmse:0.897911
[20]	train-rmse:0.375691	valid-rmse:0.421931
[30]	train-rmse:0.337602	valid-rmse:0.386937
[39]	train-rmse:0.330746	valid-rmse:0.381867
Iteration No: 436 ended. Search finished for the next optimal point.
Time taken: 25.5562
Function value obtained: 0.3819
Current minimum: 0.3801
Iteration No: 437 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.19859694529992056, 'colsample_bytree': 1.0, 'max_depth': 75, 'subsample': 1.0, 'lambda': 59.020666346707259, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.81935	valid-rmse:4.83757
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.663016	valid-rmse:0.696633
[20]	train-rmse:0.357882	valid-rmse:0.404584
[30]	train-rmse:0.337743	valid-rmse:0.386304
[39]	train-rmse:0.331947	valid-rmse:0.382156
Iteration No: 437 ended. Search finished for the next optimal point.
Time taken: 28.3978
Function value obtained: 0.3822
Current minimum: 0.3801
Iteration No: 438 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 97, 'eta': 0.16892625714804302, 'colsample_bytree': 0.40000000000000002, 'max_depth': 95, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9922	valid-rmse:5.00974
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.864099	valid-rmse:0.892755
[20]	train-rmse:0.364511	valid-rmse:0.413908
[30]	train-rmse:0.333505	valid-rmse:0.385998
[39]	train-rmse:0.328263	valid-rmse:0.382375
Iteration No: 438 ended. Search finished for the next optimal point.
Time taken: 24.4185
Function value obtained: 0.3824
Current minimum: 0.3801
Iteration No: 439 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 103, 'eta': 0.22247390030027853, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.67858	valid-rmse:4.69677
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.54924	valid-rmse:0.587275
[20]	train-rmse:0.350499	valid-rmse:0.398315
[30]	train-rmse:0.33554	valid-rmse:0.385432
[39]	train-rmse:0.329731	valid-rmse:0.381554
Iteration No: 439 ended. Search finished for the next optimal point.
Time taken: 28.5414
Function value obtained: 0.3816
Current minimum: 0.3801
Iteration No: 440 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 161, 'eta': 0.18615056808105906, 'colsample_bytree': 1.0, 'max_depth': 165, 'subsample': 1.0, 'lambda': 39.32288688812293, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89273	valid-rmse:4.91092
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.741555	valid-rmse:0.773334
[20]	train-rmse:0.362719	valid-rmse:0.409425
[30]	train-rmse:0.337687	valid-rmse:0.386339
[39]	train-rmse:0.331919	valid-rmse:0.382098
Iteration No: 440 ended. Search finished for the next optimal point.
Time taken: 27.6578
Function value obtained: 0.3821
Current minimum: 0.3801
Iteration No: 441 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 115, 'eta': 0.16932399832500908, 'colsample_bytree': 0.78003665338077566, 'max_depth': 121, 'subsample': 1.0, 'lambda': 23.612497393692323, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99236	valid-rmse:5.01028
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.877844	valid-rmse:0.906775
[20]	train-rmse:0.377056	valid-rmse:0.423281
[30]	train-rmse:0.337677	valid-rmse:0.387071
[39]	train-rmse:0.330555	valid-rmse:0.381469
Iteration No: 441 ended. Search finished for the next optimal point.
Time taken: 25.6557
Function value obtained: 0.3815
Current minimum: 0.3801
Iteration No: 442 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 261, 'eta': 0.29835341800496401, 'colsample_bytree': 0.40936184191268099, 'max_depth': 198, 'subsample': 0.84753266521252046, 'lambda': 89.983457555774137, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22957	valid-rmse:4.24811
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.404406	valid-rmse:0.447769
[20]	train-rmse:0.354415	valid-rmse:0.399549
[30]	train-rmse:0.344627	valid-rmse:0.390412
[39]	train-rmse:0.341384	valid-rmse:0.387711
Iteration No: 442 ended. Search finished for the next optimal point.
Time taken: 20.2856
Function value obtained: 0.3877
Current minimum: 0.3801
Iteration No: 443 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 146, 'eta': 0.16484351070463613, 'colsample_bytree': 0.66587274964818721, 'max_depth': 122, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01621	valid-rmse:5.03377
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.900738	valid-rmse:0.928332
[20]	train-rmse:0.366953	valid-rmse:0.414977
[30]	train-rmse:0.333674	valid-rmse:0.384506
[39]	train-rmse:0.329108	valid-rmse:0.381173
Iteration No: 443 ended. Search finished for the next optimal point.
Time taken: 28.5580
Function value obtained: 0.3812
Current minimum: 0.3801
Iteration No: 444 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 12, 'eta': 0.18889666993680021, 'colsample_bytree': 0.62563546121706548, 'max_depth': 6, 'subsample': 0.91494535556211876, 'lambda': 89.821704899893589, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87836	valid-rmse:4.89662
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.733066	valid-rmse:0.76553
[20]	train-rmse:0.384558	valid-rmse:0.428708
[30]	train-rmse:0.363593	valid-rmse:0.408036
[39]	train-rmse:0.356751	valid-rmse:0.401358
Iteration No: 444 ended. Search finished for the next optimal point.
Time taken: 18.2582
Function value obtained: 0.4014
Current minimum: 0.3801
Iteration No: 445 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 167, 'eta': 0.19615420509879458, 'colsample_bytree': 1.0, 'max_depth': 42, 'subsample': 1.0, 'lambda': 28.987908096374611, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8328	valid-rmse:4.8508
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.672024	valid-rmse:0.705316
[20]	train-rmse:0.354135	valid-rmse:0.401105
[30]	train-rmse:0.335185	valid-rmse:0.384246
[39]	train-rmse:0.330742	valid-rmse:0.381571
Iteration No: 445 ended. Search finished for the next optimal point.
Time taken: 30.4776
Function value obtained: 0.3816
Current minimum: 0.3801
Iteration No: 446 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 154, 'eta': 0.19502913729096472, 'colsample_bytree': 1.0, 'max_depth': 68, 'subsample': 1.0, 'lambda': 54.234932070948325, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8404	valid-rmse:4.8586
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.683999	valid-rmse:0.717345
[20]	train-rmse:0.359427	valid-rmse:0.406238
[30]	train-rmse:0.337943	valid-rmse:0.386287
[39]	train-rmse:0.33156	valid-rmse:0.381334
Iteration No: 446 ended. Search finished for the next optimal point.
Time taken: 28.5583
Function value obtained: 0.3813
Current minimum: 0.3801
Iteration No: 447 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 163, 'eta': 0.19424540175093274, 'colsample_bytree': 1.0, 'max_depth': 44, 'subsample': 1.0, 'lambda': 28.60285175896523, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84413	valid-rmse:4.86213
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.683601	valid-rmse:0.71654
[20]	train-rmse:0.356017	valid-rmse:0.402875
[30]	train-rmse:0.336217	valid-rmse:0.38493
[39]	train-rmse:0.33127	valid-rmse:0.381578
Iteration No: 447 ended. Search finished for the next optimal point.
Time taken: 30.7991
Function value obtained: 0.3816
Current minimum: 0.3801
Iteration No: 448 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 183, 'eta': 0.22805068691420322, 'colsample_bytree': 1.0, 'max_depth': 73, 'subsample': 1.0, 'lambda': 65.91450666555356, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.64474	valid-rmse:4.66296
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.525463	valid-rmse:0.563584
[20]	train-rmse:0.349389	valid-rmse:0.395984
[30]	train-rmse:0.336576	valid-rmse:0.384943
[39]	train-rmse:0.3316	valid-rmse:0.381723
Iteration No: 448 ended. Search finished for the next optimal point.
Time taken: 29.2340
Function value obtained: 0.3817
Current minimum: 0.3801
Iteration No: 449 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 120, 'eta': 0.17771786193629951, 'colsample_bytree': 0.40000000000000002, 'max_depth': 70, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93974	valid-rmse:4.95727
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.786471	valid-rmse:0.81648
[20]	train-rmse:0.357815	valid-rmse:0.406656
[30]	train-rmse:0.334585	valid-rmse:0.385722
[39]	train-rmse:0.32979	valid-rmse:0.382623
Iteration No: 449 ended. Search finished for the next optimal point.
Time taken: 25.6133
Function value obtained: 0.3826
Current minimum: 0.3801
Iteration No: 450 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 147, 'eta': 0.19057953623621204, 'colsample_bytree': 1.0, 'max_depth': 68, 'subsample': 1.0, 'lambda': 52.413223345280961, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86679	valid-rmse:4.88499
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.713008	valid-rmse:0.74556
[20]	train-rmse:0.361015	valid-rmse:0.407765
[30]	train-rmse:0.337698	valid-rmse:0.386482
[39]	train-rmse:0.332002	valid-rmse:0.382282
Iteration No: 450 ended. Search finished for the next optimal point.
Time taken: 29.8630
Function value obtained: 0.3823
Current minimum: 0.3801
Iteration No: 451 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 164, 'eta': 0.21029560215577309, 'colsample_bytree': 1.0, 'max_depth': 169, 'subsample': 1.0, 'lambda': 61.797249461387338, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.75006	valid-rmse:4.76825
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.599721	valid-rmse:0.635381
[20]	train-rmse:0.353617	valid-rmse:0.400086
[30]	train-rmse:0.336924	valid-rmse:0.385043
[39]	train-rmse:0.331478	valid-rmse:0.381284
Iteration No: 451 ended. Search finished for the next optimal point.
Time taken: 30.3141
Function value obtained: 0.3813
Current minimum: 0.3801
Iteration No: 452 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 161, 'eta': 0.1932875895932738, 'colsample_bytree': 1.0, 'max_depth': 45, 'subsample': 1.0, 'lambda': 28.296518804616181, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84981	valid-rmse:4.86782
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.689737	valid-rmse:0.722559
[20]	train-rmse:0.355989	valid-rmse:0.402791
[30]	train-rmse:0.335997	valid-rmse:0.385027
[39]	train-rmse:0.330886	valid-rmse:0.381475
Iteration No: 452 ended. Search finished for the next optimal point.
Time taken: 30.3233
Function value obtained: 0.3815
Current minimum: 0.3801
Iteration No: 453 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 16, 'eta': 0.10326379540776304, 'colsample_bytree': 0.68401629987378976, 'max_depth': 120, 'subsample': 0.97893298710598708, 'lambda': 4.4607633640444355, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.38466	valid-rmse:5.40249
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.8515	valid-rmse:1.87212
[20]	train-rmse:0.713675	valid-rmse:0.746789
[30]	train-rmse:0.403854	valid-rmse:0.453166
[39]	train-rmse:0.340534	valid-rmse:0.397933
Iteration No: 453 ended. Search finished for the next optimal point.
Time taken: 27.5343
Function value obtained: 0.3979
Current minimum: 0.3801
Iteration No: 454 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 153, 'eta': 0.19001321848999808, 'colsample_bytree': 1.0, 'max_depth': 46, 'subsample': 1.0, 'lambda': 27.918025102731281, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86927	valid-rmse:4.88727
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.711647	valid-rmse:0.743728
[20]	train-rmse:0.358202	valid-rmse:0.404763
[30]	train-rmse:0.336225	valid-rmse:0.385165
[39]	train-rmse:0.330779	valid-rmse:0.381187
Iteration No: 454 ended. Search finished for the next optimal point.
Time taken: 29.9011
Function value obtained: 0.3812
Current minimum: 0.3801
Iteration No: 455 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 152, 'eta': 0.18958740845818636, 'colsample_bytree': 1.0, 'max_depth': 47, 'subsample': 1.0, 'lambda': 28.114329847044633, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87181	valid-rmse:4.88981
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.714256	valid-rmse:0.746567
[20]	train-rmse:0.358047	valid-rmse:0.404918
[30]	train-rmse:0.336215	valid-rmse:0.385228
[39]	train-rmse:0.330944	valid-rmse:0.381506
Iteration No: 455 ended. Search finished for the next optimal point.
Time taken: 30.0587
Function value obtained: 0.3815
Current minimum: 0.3801
Iteration No: 456 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26798054362216628, 'colsample_bytree': 1.0, 'max_depth': 59, 'subsample': 1.0, 'lambda': 42.825599332187522, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4066	valid-rmse:4.42496
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.423316	valid-rmse:0.466281
[20]	train-rmse:0.34426	valid-rmse:0.390351
[30]	train-rmse:0.335919	valid-rmse:0.38408
[39]	train-rmse:0.332314	valid-rmse:0.38181
Iteration No: 456 ended. Search finished for the next optimal point.
Time taken: 31.4897
Function value obtained: 0.3818
Current minimum: 0.3801
Iteration No: 457 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.18808134567183216, 'colsample_bytree': 1.0, 'max_depth': 48, 'subsample': 1.0, 'lambda': 27.871446357234969, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88075	valid-rmse:4.89874
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.725149	valid-rmse:0.756962
[20]	train-rmse:0.359267	valid-rmse:0.405616
[30]	train-rmse:0.336404	valid-rmse:0.38482
[39]	train-rmse:0.330503	valid-rmse:0.380751
Iteration No: 457 ended. Search finished for the next optimal point.
Time taken: 29.8325
Function value obtained: 0.3808
Current minimum: 0.3801
Iteration No: 458 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 143, 'eta': 0.18883009588859867, 'colsample_bytree': 1.0, 'max_depth': 66, 'subsample': 1.0, 'lambda': 51.237172715733941, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87715	valid-rmse:4.89535
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.724229	valid-rmse:0.756467
[20]	train-rmse:0.362729	valid-rmse:0.409251
[30]	train-rmse:0.338302	valid-rmse:0.386616
[39]	train-rmse:0.332055	valid-rmse:0.381881
Iteration No: 458 ended. Search finished for the next optimal point.
Time taken: 29.7225
Function value obtained: 0.3819
Current minimum: 0.3801
Iteration No: 459 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 179, 'eta': 0.2380432564583517, 'colsample_bytree': 1.0, 'max_depth': 58, 'subsample': 1.0, 'lambda': 56.039477254058617, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.58492	valid-rmse:4.60321
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.490727	valid-rmse:0.530828
[20]	train-rmse:0.346271	valid-rmse:0.393594
[30]	train-rmse:0.335198	valid-rmse:0.384301
[39]	train-rmse:0.330669	valid-rmse:0.381537
Iteration No: 459 ended. Search finished for the next optimal point.
Time taken: 31.9209
Function value obtained: 0.3815
Current minimum: 0.3801
Iteration No: 460 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 152, 'eta': 0.18727074658907225, 'colsample_bytree': 1.0, 'max_depth': 48, 'subsample': 1.0, 'lambda': 25.251412493762054, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88546	valid-rmse:4.90345
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.730391	valid-rmse:0.762313
[20]	train-rmse:0.359139	valid-rmse:0.40593
[30]	train-rmse:0.335724	valid-rmse:0.384807
[39]	train-rmse:0.330675	valid-rmse:0.3814
Iteration No: 460 ended. Search finished for the next optimal point.
Time taken: 31.3458
Function value obtained: 0.3814
Current minimum: 0.3801
Iteration No: 461 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 177, 'eta': 0.20451743897387703, 'colsample_bytree': 0.40000000000000002, 'max_depth': 47, 'subsample': 1.0, 'lambda': 34.521735108858906, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.78369	valid-rmse:4.80182
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.632474	valid-rmse:0.66697
[20]	train-rmse:0.360143	valid-rmse:0.406029
[30]	train-rmse:0.339558	valid-rmse:0.387647
[39]	train-rmse:0.333209	valid-rmse:0.383051
Iteration No: 461 ended. Search finished for the next optimal point.
Time taken: 21.6309
Function value obtained: 0.3831
Current minimum: 0.3801
Iteration No: 462 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26972603480048163, 'colsample_bytree': 1.0, 'max_depth': 77, 'subsample': 1.0, 'lambda': 56.119091635900915, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.3968	valid-rmse:4.41516
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.424257	valid-rmse:0.467108
[20]	train-rmse:0.344169	valid-rmse:0.390409
[30]	train-rmse:0.335851	valid-rmse:0.383547
[39]	train-rmse:0.332674	valid-rmse:0.381591
Iteration No: 462 ended. Search finished for the next optimal point.
Time taken: 29.7510
Function value obtained: 0.3816
Current minimum: 0.3801
Iteration No: 463 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 129, 'eta': 0.26034009361555033, 'colsample_bytree': 1.0, 'max_depth': 70, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.45393	valid-rmse:4.47219
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.441736	valid-rmse:0.484232
[20]	train-rmse:0.344236	valid-rmse:0.392009
[30]	train-rmse:0.333487	valid-rmse:0.383408
[39]	train-rmse:0.329545	valid-rmse:0.381325
Iteration No: 463 ended. Search finished for the next optimal point.
Time taken: 33.0229
Function value obtained: 0.3813
Current minimum: 0.3801
Iteration No: 464 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 136, 'eta': 0.18001833143489054, 'colsample_bytree': 1.0, 'max_depth': 53, 'subsample': 1.0, 'lambda': 23.512294419531557, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92851	valid-rmse:4.94649
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.784546	valid-rmse:0.814967
[20]	train-rmse:0.364551	valid-rmse:0.410889
[30]	train-rmse:0.336537	valid-rmse:0.385597
[39]	train-rmse:0.330424	valid-rmse:0.381156
Iteration No: 464 ended. Search finished for the next optimal point.
Time taken: 30.6647
Function value obtained: 0.3812
Current minimum: 0.3801
Iteration No: 465 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.16749052531722233, 'colsample_bytree': 1.0, 'max_depth': 165, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00029	valid-rmse:5.01786
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.873706	valid-rmse:0.90204
[20]	train-rmse:0.363076	valid-rmse:0.411902
[30]	train-rmse:0.334001	valid-rmse:0.385442
[39]	train-rmse:0.32952	valid-rmse:0.38244
Iteration No: 465 ended. Search finished for the next optimal point.
Time taken: 37.8902
Function value obtained: 0.3824
Current minimum: 0.3801
Iteration No: 466 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 16, 'eta': 0.18881025671216295, 'colsample_bytree': 0.92346277987454661, 'max_depth': 167, 'subsample': 0.88748719175709323, 'lambda': 86.569136396978649, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87853	valid-rmse:4.89668
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.730761	valid-rmse:0.763359
[20]	train-rmse:0.36507	valid-rmse:0.413279
[30]	train-rmse:0.335838	valid-rmse:0.387595
[39]	train-rmse:0.328013	valid-rmse:0.382546
Iteration No: 466 ended. Search finished for the next optimal point.
Time taken: 30.8182
Function value obtained: 0.3825
Current minimum: 0.3801
Iteration No: 467 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 129, 'eta': 0.26045779717690298, 'colsample_bytree': 1.0, 'max_depth': 71, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.45323	valid-rmse:4.47149
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.441525	valid-rmse:0.484036
[20]	train-rmse:0.344487	valid-rmse:0.392361
[30]	train-rmse:0.333936	valid-rmse:0.384121
[39]	train-rmse:0.329682	valid-rmse:0.38157
Iteration No: 467 ended. Search finished for the next optimal point.
Time taken: 32.9438
Function value obtained: 0.3816
Current minimum: 0.3801
Iteration No: 468 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 172, 'eta': 0.21679303652521675, 'colsample_bytree': 1.0, 'max_depth': 166, 'subsample': 1.0, 'lambda': 57.284164912912786, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.71118	valid-rmse:4.72943
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.568747	valid-rmse:0.605388
[20]	train-rmse:0.350465	valid-rmse:0.397121
[30]	train-rmse:0.336126	valid-rmse:0.384505
[39]	train-rmse:0.330864	valid-rmse:0.380979
Iteration No: 468 ended. Search finished for the next optimal point.
Time taken: 31.6534
Function value obtained: 0.3810
Current minimum: 0.3801
Iteration No: 469 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 184, 'eta': 0.18416890624260135, 'colsample_bytree': 1.0, 'max_depth': 54, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90086	valid-rmse:4.91835
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.731269	valid-rmse:0.762183
[20]	train-rmse:0.349935	valid-rmse:0.398748
[30]	train-rmse:0.333395	valid-rmse:0.383756
[39]	train-rmse:0.330208	valid-rmse:0.381503
Iteration No: 469 ended. Search finished for the next optimal point.
Time taken: 36.4380
Function value obtained: 0.3815
Current minimum: 0.3801
Iteration No: 470 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 128, 'eta': 0.2347956103518021, 'colsample_bytree': 1.0, 'max_depth': 165, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.60546	valid-rmse:4.62367
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.506348	valid-rmse:0.545747
[20]	train-rmse:0.347669	valid-rmse:0.395384
[30]	train-rmse:0.335115	valid-rmse:0.384863
[39]	train-rmse:0.330388	valid-rmse:0.381949
Iteration No: 470 ended. Search finished for the next optimal point.
Time taken: 31.9589
Function value obtained: 0.3819
Current minimum: 0.3801
Iteration No: 471 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 291, 'eta': 0.29705111880626411, 'colsample_bytree': 0.96923086004324532, 'max_depth': 147, 'subsample': 0.8550966284073489, 'lambda': 1.2688645591899239, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22926	valid-rmse:4.24695
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.373744	valid-rmse:0.419263
[20]	train-rmse:0.339793	valid-rmse:0.387326
[30]	train-rmse:0.335656	valid-rmse:0.384541
[39]	train-rmse:0.33373	valid-rmse:0.383877
Iteration No: 471 ended. Search finished for the next optimal point.
Time taken: 36.1404
Function value obtained: 0.3839
Current minimum: 0.3801
Iteration No: 472 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 127, 'eta': 0.18025811028875977, 'colsample_bytree': 1.0, 'max_depth': 53, 'subsample': 1.0, 'lambda': 28.371930866020747, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92728	valid-rmse:4.94527
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.783761	valid-rmse:0.814499
[20]	train-rmse:0.364879	valid-rmse:0.4117
[30]	train-rmse:0.336475	valid-rmse:0.386009
[39]	train-rmse:0.330277	valid-rmse:0.381649
Iteration No: 472 ended. Search finished for the next optimal point.
Time taken: 31.3358
Function value obtained: 0.3816
Current minimum: 0.3801
Iteration No: 473 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 29, 'eta': 0.23222300180906655, 'colsample_bytree': 0.99168102441205008, 'max_depth': 135, 'subsample': 0.81744586741070124, 'lambda': 4.8615642402280246, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.61611	valid-rmse:4.63399
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.490187	valid-rmse:0.531531
[20]	train-rmse:0.334299	valid-rmse:0.390778
[30]	train-rmse:0.32736	valid-rmse:0.388689
[39]	train-rmse:0.326136	valid-rmse:0.389645
Iteration No: 473 ended. Search finished for the next optimal point.
Time taken: 51.2828
Function value obtained: 0.3896
Current minimum: 0.3801
Iteration No: 474 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.16448763257628995, 'colsample_bytree': 1.0, 'max_depth': 137, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01822	valid-rmse:5.0358
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.903834	valid-rmse:0.931545
[20]	train-rmse:0.366662	valid-rmse:0.415438
[30]	train-rmse:0.333323	valid-rmse:0.384898
[39]	train-rmse:0.329112	valid-rmse:0.382032
Iteration No: 474 ended. Search finished for the next optimal point.
Time taken: 37.4373
Function value obtained: 0.3820
Current minimum: 0.3801
Iteration No: 475 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 146, 'eta': 0.16785736564601744, 'colsample_bytree': 1.0, 'max_depth': 166, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99814	valid-rmse:5.01573
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.870675	valid-rmse:0.899048
[20]	train-rmse:0.362972	valid-rmse:0.411881
[30]	train-rmse:0.333274	valid-rmse:0.384609
[39]	train-rmse:0.329496	valid-rmse:0.382118
Iteration No: 475 ended. Search finished for the next optimal point.
Time taken: 37.6018
Function value obtained: 0.3821
Current minimum: 0.3801
Iteration No: 476 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.27019111780818683, 'colsample_bytree': 1.0, 'max_depth': 63, 'subsample': 1.0, 'lambda': 42.22303586577295, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.39345	valid-rmse:4.41181
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.420415	valid-rmse:0.463659
[20]	train-rmse:0.343673	valid-rmse:0.390171
[30]	train-rmse:0.335672	valid-rmse:0.383911
[39]	train-rmse:0.332315	valid-rmse:0.381945
Iteration No: 476 ended. Search finished for the next optimal point.
Time taken: 33.2234
Function value obtained: 0.3819
Current minimum: 0.3801
Iteration No: 477 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 128, 'eta': 0.18020171879781063, 'colsample_bytree': 1.0, 'max_depth': 54, 'subsample': 1.0, 'lambda': 28.085484850045397, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92761	valid-rmse:4.94559
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.784651	valid-rmse:0.815195
[20]	train-rmse:0.36516	valid-rmse:0.411673
[30]	train-rmse:0.336529	valid-rmse:0.385522
[39]	train-rmse:0.330144	valid-rmse:0.380824
Iteration No: 477 ended. Search finished for the next optimal point.
Time taken: 31.8474
Function value obtained: 0.3808
Current minimum: 0.3801
Iteration No: 478 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 170, 'eta': 0.23931868549879023, 'colsample_bytree': 1.0, 'max_depth': 65, 'subsample': 1.0, 'lambda': 59.325419382410495, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.57748	valid-rmse:4.59577
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.487528	valid-rmse:0.527704
[20]	train-rmse:0.346592	valid-rmse:0.393906
[30]	train-rmse:0.334324	valid-rmse:0.383801
[39]	train-rmse:0.330372	valid-rmse:0.381498
Iteration No: 478 ended. Search finished for the next optimal point.
Time taken: 33.2506
Function value obtained: 0.3815
Current minimum: 0.3801
Iteration No: 479 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 145, 'eta': 0.19271541764992461, 'colsample_bytree': 1.0, 'max_depth': 65, 'subsample': 1.0, 'lambda': 51.927060228173531, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85408	valid-rmse:4.87228
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.69836	valid-rmse:0.731138
[20]	train-rmse:0.360643	valid-rmse:0.406966
[30]	train-rmse:0.337519	valid-rmse:0.38588
[39]	train-rmse:0.331431	valid-rmse:0.381423
Iteration No: 479 ended. Search finished for the next optimal point.
Time taken: 30.9521
Function value obtained: 0.3814
Current minimum: 0.3801
Iteration No: 480 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 168, 'eta': 0.20497576430038622, 'colsample_bytree': 1.0, 'max_depth': 168, 'subsample': 1.0, 'lambda': 49.5033151970379, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.78114	valid-rmse:4.79936
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.624398	valid-rmse:0.659135
[20]	train-rmse:0.353414	valid-rmse:0.400021
[30]	train-rmse:0.336718	valid-rmse:0.385174
[39]	train-rmse:0.331477	valid-rmse:0.381778
Iteration No: 480 ended. Search finished for the next optimal point.
Time taken: 31.0819
Function value obtained: 0.3818
Current minimum: 0.3801
Iteration No: 481 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.20186583438983191, 'colsample_bytree': 1.0, 'max_depth': 64, 'subsample': 1.0, 'lambda': 51.362126138299708, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.79968	valid-rmse:4.8179
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.642521	valid-rmse:0.676685
[20]	train-rmse:0.356344	valid-rmse:0.402695
[30]	train-rmse:0.337586	valid-rmse:0.385563
[39]	train-rmse:0.332196	valid-rmse:0.381711
Iteration No: 481 ended. Search finished for the next optimal point.
Time taken: 31.4664
Function value obtained: 0.3817
Current minimum: 0.3801
Iteration No: 482 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 27, 'eta': 0.15978506598974629, 'colsample_bytree': 0.4314699849452287, 'max_depth': 156, 'subsample': 0.8100971050787481, 'lambda': 3.9347646892862547, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.04797	valid-rmse:5.06573
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.967872	valid-rmse:0.995212
[20]	train-rmse:0.384095	valid-rmse:0.433348
[30]	train-rmse:0.331881	valid-rmse:0.38825
[39]	train-rmse:0.324918	valid-rmse:0.384298
Iteration No: 482 ended. Search finished for the next optimal point.
Time taken: 27.3607
Function value obtained: 0.3843
Current minimum: 0.3801
Iteration No: 483 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 144, 'eta': 0.18327202759711406, 'colsample_bytree': 1.0, 'max_depth': 172, 'subsample': 1.0, 'lambda': 37.787660998733841, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9098	valid-rmse:4.92798
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.762791	valid-rmse:0.794156
[20]	train-rmse:0.365009	valid-rmse:0.411976
[30]	train-rmse:0.337534	valid-rmse:0.386459
[39]	train-rmse:0.331155	valid-rmse:0.381527
Iteration No: 483 ended. Search finished for the next optimal point.
Time taken: 33.2821
Function value obtained: 0.3815
Current minimum: 0.3801
Iteration No: 484 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.25084696041418325, 'colsample_bytree': 1.0, 'max_depth': 84, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.51023	valid-rmse:4.52848
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.46328	valid-rmse:0.504825
[20]	train-rmse:0.345765	valid-rmse:0.393432
[30]	train-rmse:0.335026	valid-rmse:0.384944
[39]	train-rmse:0.330459	valid-rmse:0.382143
Iteration No: 484 ended. Search finished for the next optimal point.
Time taken: 33.4697
Function value obtained: 0.3821
Current minimum: 0.3801
Iteration No: 485 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 129, 'eta': 0.17879308931447202, 'colsample_bytree': 1.0, 'max_depth': 55, 'subsample': 1.0, 'lambda': 25.670473657782473, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93588	valid-rmse:4.95387
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.795456	valid-rmse:0.825824
[20]	train-rmse:0.3655	valid-rmse:0.412368
[30]	train-rmse:0.336268	valid-rmse:0.385432
[39]	train-rmse:0.329448	valid-rmse:0.380419
Iteration No: 485 ended. Search finished for the next optimal point.
Time taken: 32.5630
Function value obtained: 0.3804
Current minimum: 0.3801
Iteration No: 486 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 294, 'eta': 0.15442900598286174, 'colsample_bytree': 0.97653320655816822, 'max_depth': 74, 'subsample': 0.82862560334287805, 'lambda': 4.5984205731937005, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.0797	valid-rmse:5.09758
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.02499	valid-rmse:1.05103
[20]	train-rmse:0.398775	valid-rmse:0.442791
[30]	train-rmse:0.344613	valid-rmse:0.391293
[39]	train-rmse:0.337093	valid-rmse:0.384386
Iteration No: 486 ended. Search finished for the next optimal point.
Time taken: 28.4598
Function value obtained: 0.3844
Current minimum: 0.3801
Iteration No: 487 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 132, 'eta': 0.26816267407135719, 'colsample_bytree': 1.0, 'max_depth': 170, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.40753	valid-rmse:4.42581
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.428876	valid-rmse:0.471837
[20]	train-rmse:0.343247	valid-rmse:0.39056
[30]	train-rmse:0.333708	valid-rmse:0.38331
[39]	train-rmse:0.329764	valid-rmse:0.38103
Iteration No: 487 ended. Search finished for the next optimal point.
Time taken: 34.3820
Function value obtained: 0.3810
Current minimum: 0.3801
Iteration No: 488 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 127, 'eta': 0.17897279877987668, 'colsample_bytree': 1.0, 'max_depth': 55, 'subsample': 1.0, 'lambda': 26.314030962562615, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93484	valid-rmse:4.95283
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.793857	valid-rmse:0.824286
[20]	train-rmse:0.365929	valid-rmse:0.41264
[30]	train-rmse:0.336493	valid-rmse:0.385459
[39]	train-rmse:0.330424	valid-rmse:0.381257
Iteration No: 488 ended. Search finished for the next optimal point.
Time taken: 31.5469
Function value obtained: 0.3813
Current minimum: 0.3801
Iteration No: 489 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 147, 'eta': 0.16352525362158515, 'colsample_bytree': 1.0, 'max_depth': 126, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02399	valid-rmse:5.04159
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.913678	valid-rmse:0.941246
[20]	train-rmse:0.368627	valid-rmse:0.416985
[30]	train-rmse:0.334549	valid-rmse:0.385772
[39]	train-rmse:0.330129	valid-rmse:0.38263
Iteration No: 489 ended. Search finished for the next optimal point.
Time taken: 37.7314
Function value obtained: 0.3826
Current minimum: 0.3801
Iteration No: 490 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 163, 'eta': 0.17837662338104338, 'colsample_bytree': 1.0, 'max_depth': 62, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93542	valid-rmse:4.95296
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.77649	valid-rmse:0.806668
[20]	train-rmse:0.353159	valid-rmse:0.40232
[30]	train-rmse:0.333394	valid-rmse:0.38431
[39]	train-rmse:0.329667	valid-rmse:0.381886
Iteration No: 490 ended. Search finished for the next optimal point.
Time taken: 38.2123
Function value obtained: 0.3819
Current minimum: 0.3801
Iteration No: 491 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 136, 'eta': 0.18326046134636506, 'colsample_bytree': 1.0, 'max_depth': 67, 'subsample': 1.0, 'lambda': 46.611243887049852, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91012	valid-rmse:4.92831
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.764593	valid-rmse:0.795854
[20]	train-rmse:0.365694	valid-rmse:0.412618
[30]	train-rmse:0.337472	valid-rmse:0.38641
[39]	train-rmse:0.331473	valid-rmse:0.38195
Iteration No: 491 ended. Search finished for the next optimal point.
Time taken: 31.8106
Function value obtained: 0.3820
Current minimum: 0.3801
Iteration No: 492 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 191, 'eta': 0.22411480280322083, 'colsample_bytree': 1.0, 'max_depth': 168, 'subsample': 1.0, 'lambda': 57.930736072074012, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.66772	valid-rmse:4.68598
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.538834	valid-rmse:0.576599
[20]	train-rmse:0.349975	valid-rmse:0.396176
[30]	train-rmse:0.336251	valid-rmse:0.384248
[39]	train-rmse:0.331773	valid-rmse:0.381434
Iteration No: 492 ended. Search finished for the next optimal point.
Time taken: 33.7463
Function value obtained: 0.3814
Current minimum: 0.3801
Iteration No: 493 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 144, 'eta': 0.25739664499927811, 'colsample_bytree': 1.0, 'max_depth': 166, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.47138	valid-rmse:4.48964
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.448639	valid-rmse:0.490748
[20]	train-rmse:0.344995	valid-rmse:0.392347
[30]	train-rmse:0.334274	valid-rmse:0.383869
[39]	train-rmse:0.330409	valid-rmse:0.381883
Iteration No: 493 ended. Search finished for the next optimal point.
Time taken: 34.3859
Function value obtained: 0.3819
Current minimum: 0.3801
Iteration No: 494 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 288, 'eta': 0.18279565770972275, 'colsample_bytree': 0.83922194132709349, 'max_depth': 153, 'subsample': 0.95770261399864598, 'lambda': 88.823161961007486, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91448	valid-rmse:4.93271
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.775845	valid-rmse:0.806952
[20]	train-rmse:0.376312	valid-rmse:0.421562
[30]	train-rmse:0.346842	valid-rmse:0.393313
[39]	train-rmse:0.338927	valid-rmse:0.386151
Iteration No: 494 ended. Search finished for the next optimal point.
Time taken: 28.1059
Function value obtained: 0.3862
Current minimum: 0.3801
Iteration No: 495 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.27131585475148967, 'colsample_bytree': 1.0, 'max_depth': 65, 'subsample': 1.0, 'lambda': 42.594903178042379, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.38679	valid-rmse:4.40515
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.418933	valid-rmse:0.462135
[20]	train-rmse:0.343938	valid-rmse:0.390666
[30]	train-rmse:0.335525	valid-rmse:0.383965
[39]	train-rmse:0.332505	valid-rmse:0.38204
Iteration No: 495 ended. Search finished for the next optimal point.
Time taken: 34.9166
Function value obtained: 0.3820
Current minimum: 0.3801
Iteration No: 496 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.18788017115218369, 'colsample_bytree': 1.0, 'max_depth': 169, 'subsample': 1.0, 'lambda': 37.367077511209658, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88238	valid-rmse:4.90058
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.728357	valid-rmse:0.760516
[20]	train-rmse:0.361053	valid-rmse:0.408171
[30]	train-rmse:0.336865	valid-rmse:0.385945
[39]	train-rmse:0.331209	valid-rmse:0.381983
Iteration No: 496 ended. Search finished for the next optimal point.
Time taken: 32.6301
Function value obtained: 0.3820
Current minimum: 0.3801
Iteration No: 497 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 125, 'eta': 0.18062777203951758, 'colsample_bytree': 1.0, 'max_depth': 55, 'subsample': 1.0, 'lambda': 28.421307289386302, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92509	valid-rmse:4.94308
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.780984	valid-rmse:0.811642
[20]	train-rmse:0.364741	valid-rmse:0.411567
[30]	train-rmse:0.336742	valid-rmse:0.385993
[39]	train-rmse:0.330665	valid-rmse:0.38165
Iteration No: 497 ended. Search finished for the next optimal point.
Time taken: 33.1118
Function value obtained: 0.3817
Current minimum: 0.3801
Iteration No: 498 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 173, 'eta': 0.23903522078970352, 'colsample_bytree': 1.0, 'max_depth': 65, 'subsample': 1.0, 'lambda': 57.408833369571667, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.57908	valid-rmse:4.59737
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.488364	valid-rmse:0.528508
[20]	train-rmse:0.346135	valid-rmse:0.393603
[30]	train-rmse:0.334691	valid-rmse:0.384307
[39]	train-rmse:0.330372	valid-rmse:0.381563
Iteration No: 498 ended. Search finished for the next optimal point.
Time taken: 34.9907
Function value obtained: 0.3816
Current minimum: 0.3801
Iteration No: 499 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 145, 'eta': 0.18241951235794288, 'colsample_bytree': 0.67044288053755463, 'max_depth': 61, 'subsample': 1.0, 'lambda': 21.886167342482178, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91438	valid-rmse:4.9323
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.766228	valid-rmse:0.7968
[20]	train-rmse:0.362889	valid-rmse:0.409279
[30]	train-rmse:0.336387	valid-rmse:0.384992
[39]	train-rmse:0.330721	valid-rmse:0.380897
Iteration No: 499 ended. Search finished for the next optimal point.
Time taken: 28.8180
Function value obtained: 0.3809
Current minimum: 0.3801
Iteration No: 500 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.18037309273917013, 'colsample_bytree': 0.40000000000000002, 'max_depth': 64, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92392	valid-rmse:4.94146
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.765017	valid-rmse:0.795455
[20]	train-rmse:0.356098	valid-rmse:0.404997
[30]	train-rmse:0.334595	valid-rmse:0.3858
[39]	train-rmse:0.329931	valid-rmse:0.382647
Iteration No: 500 ended. Search finished for the next optimal point.
Time taken: 27.2301
Function value obtained: 0.3826
Current minimum: 0.3801
Iteration No: 501 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 198, 'eta': 0.19678978875351105, 'colsample_bytree': 1.0, 'max_depth': 63, 'subsample': 1.0, 'lambda': 42.688362351321686, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.82958	valid-rmse:4.84779
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.670704	valid-rmse:0.704132
[20]	train-rmse:0.357969	valid-rmse:0.40397
[30]	train-rmse:0.338252	valid-rmse:0.386131
[39]	train-rmse:0.332627	valid-rmse:0.381908
Iteration No: 501 ended. Search finished for the next optimal point.
Time taken: 32.5364
Function value obtained: 0.3819
Current minimum: 0.3801
Iteration No: 502 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.2591236398755794, 'colsample_bytree': 1.0, 'max_depth': 172, 'subsample': 1.0, 'lambda': 39.213805791422843, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.45906	valid-rmse:4.47739
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.438978	valid-rmse:0.481114
[20]	train-rmse:0.345217	valid-rmse:0.391358
[30]	train-rmse:0.336586	valid-rmse:0.384055
[39]	train-rmse:0.333065	valid-rmse:0.381921
Iteration No: 502 ended. Search finished for the next optimal point.
Time taken: 34.3462
Function value obtained: 0.3819
Current minimum: 0.3801
Iteration No: 503 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 161, 'eta': 0.20257363346953827, 'colsample_bytree': 1.0, 'max_depth': 51, 'subsample': 1.0, 'lambda': 32.791821396137529, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.79486	valid-rmse:4.81308
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.634393	valid-rmse:0.669135
[20]	train-rmse:0.352244	valid-rmse:0.399531
[30]	train-rmse:0.335034	valid-rmse:0.384245
[39]	train-rmse:0.329925	valid-rmse:0.38071
Iteration No: 503 ended. Search finished for the next optimal point.
Time taken: 33.2700
Function value obtained: 0.3807
Current minimum: 0.3801
Iteration No: 504 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 141, 'eta': 0.1815955553925597, 'colsample_bytree': 0.70780412145054794, 'max_depth': 62, 'subsample': 1.0, 'lambda': 25.34105691668374, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91943	valid-rmse:4.93734
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.773216	valid-rmse:0.803815
[20]	train-rmse:0.364074	valid-rmse:0.410565
[30]	train-rmse:0.336872	valid-rmse:0.385703
[39]	train-rmse:0.330823	valid-rmse:0.38126
Iteration No: 504 ended. Search finished for the next optimal point.
Time taken: 28.2075
Function value obtained: 0.3813
Current minimum: 0.3801
Iteration No: 505 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 153, 'eta': 0.16379055649106836, 'colsample_bytree': 1.0, 'max_depth': 127, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02246	valid-rmse:5.04008
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.91113	valid-rmse:0.938583
[20]	train-rmse:0.368601	valid-rmse:0.41684
[30]	train-rmse:0.334883	valid-rmse:0.385752
[39]	train-rmse:0.330372	valid-rmse:0.382455
Iteration No: 505 ended. Search finished for the next optimal point.
Time taken: 38.9096
Function value obtained: 0.3825
Current minimum: 0.3801
Iteration No: 506 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 166, 'eta': 0.16965119769410594, 'colsample_bytree': 1.0, 'max_depth': 167, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98749	valid-rmse:5.00506
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.853538	valid-rmse:0.882427
[20]	train-rmse:0.361377	valid-rmse:0.410309
[30]	train-rmse:0.334175	valid-rmse:0.385198
[39]	train-rmse:0.330182	valid-rmse:0.382496
Iteration No: 506 ended. Search finished for the next optimal point.
Time taken: 37.8620
Function value obtained: 0.3825
Current minimum: 0.3801
Iteration No: 507 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.26823723448743941, 'colsample_bytree': 1.0, 'max_depth': 76, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.40709	valid-rmse:4.42537
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.429194	valid-rmse:0.472385
[20]	train-rmse:0.343598	valid-rmse:0.391214
[30]	train-rmse:0.333758	valid-rmse:0.383693
[39]	train-rmse:0.329655	valid-rmse:0.381438
Iteration No: 507 ended. Search finished for the next optimal point.
Time taken: 36.1173
Function value obtained: 0.3814
Current minimum: 0.3801
Iteration No: 508 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 141, 'eta': 0.18169451247114446, 'colsample_bytree': 0.71055073081742104, 'max_depth': 62, 'subsample': 1.0, 'lambda': 25.271614936360972, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91884	valid-rmse:4.93675
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.772432	valid-rmse:0.80305
[20]	train-rmse:0.363605	valid-rmse:0.410257
[30]	train-rmse:0.336757	valid-rmse:0.385745
[39]	train-rmse:0.330686	valid-rmse:0.381305
Iteration No: 508 ended. Search finished for the next optimal point.
Time taken: 29.7689
Function value obtained: 0.3813
Current minimum: 0.3801
Iteration No: 509 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.2730596269180488, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 45.395585600033897, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.37655	valid-rmse:4.39492
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.416305	valid-rmse:0.459458
[20]	train-rmse:0.343708	valid-rmse:0.389748
[30]	train-rmse:0.335836	valid-rmse:0.383795
[39]	train-rmse:0.332541	valid-rmse:0.38175
Iteration No: 509 ended. Search finished for the next optimal point.
Time taken: 35.2784
Function value obtained: 0.3818
Current minimum: 0.3801
Iteration No: 510 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 118, 'eta': 0.23689196070605925, 'colsample_bytree': 1.0, 'max_depth': 167, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.59302	valid-rmse:4.61124
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.499419	valid-rmse:0.539341
[20]	train-rmse:0.347668	valid-rmse:0.395312
[30]	train-rmse:0.33426	valid-rmse:0.384074
[39]	train-rmse:0.329502	valid-rmse:0.381181
Iteration No: 510 ended. Search finished for the next optimal point.
Time taken: 36.7841
Function value obtained: 0.3812
Current minimum: 0.3801
Iteration No: 511 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 136, 'eta': 0.18511472703908827, 'colsample_bytree': 1.0, 'max_depth': 68, 'subsample': 1.0, 'lambda': 48.156141261965743, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89914	valid-rmse:4.91733
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.750465	valid-rmse:0.781813
[20]	train-rmse:0.365011	valid-rmse:0.411281
[30]	train-rmse:0.338094	valid-rmse:0.386385
[39]	train-rmse:0.331719	valid-rmse:0.381615
Iteration No: 511 ended. Search finished for the next optimal point.
Time taken: 33.9686
Function value obtained: 0.3816
Current minimum: 0.3801
Iteration No: 512 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 178, 'eta': 0.27540889822778947, 'colsample_bytree': 1.0, 'max_depth': 90, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.3646	valid-rmse:4.38296
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.419127	valid-rmse:0.462445
[20]	train-rmse:0.343833	valid-rmse:0.391322
[30]	train-rmse:0.334395	valid-rmse:0.383916
[39]	train-rmse:0.331009	valid-rmse:0.382255
Iteration No: 512 ended. Search finished for the next optimal point.
Time taken: 36.0030
Function value obtained: 0.3823
Current minimum: 0.3801
Iteration No: 513 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 178, 'eta': 0.21204391471694861, 'colsample_bytree': 1.0, 'max_depth': 168, 'subsample': 1.0, 'lambda': 54.788823549742865, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.73931	valid-rmse:4.75755
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.590147	valid-rmse:0.626074
[20]	train-rmse:0.352241	valid-rmse:0.398994
[30]	train-rmse:0.336613	valid-rmse:0.385181
[39]	train-rmse:0.331082	valid-rmse:0.381355
Iteration No: 513 ended. Search finished for the next optimal point.
Time taken: 33.6606
Function value obtained: 0.3814
Current minimum: 0.3801
Iteration No: 514 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 174, 'eta': 0.20108695628917456, 'colsample_bytree': 0.40000000000000002, 'max_depth': 50, 'subsample': 1.0, 'lambda': 32.531060513402537, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.80399	valid-rmse:4.8221
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.650121	valid-rmse:0.684274
[20]	train-rmse:0.360681	valid-rmse:0.406656
[30]	train-rmse:0.339424	valid-rmse:0.387258
[39]	train-rmse:0.33292	valid-rmse:0.382299
Iteration No: 514 ended. Search finished for the next optimal point.
Time taken: 25.3642
Function value obtained: 0.3823
Current minimum: 0.3801
Iteration No: 515 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 148, 'eta': 0.16302655109073896, 'colsample_bytree': 1.0, 'max_depth': 117, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02697	valid-rmse:5.04457
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.918249	valid-rmse:0.945632
[20]	train-rmse:0.369041	valid-rmse:0.417075
[30]	train-rmse:0.334235	valid-rmse:0.38516
[39]	train-rmse:0.329497	valid-rmse:0.381542
Iteration No: 515 ended. Search finished for the next optimal point.
Time taken: 39.5523
Function value obtained: 0.3815
Current minimum: 0.3801
Iteration No: 516 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.27435562784797229, 'colsample_bytree': 1.0, 'max_depth': 172, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.37081	valid-rmse:4.3891
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.419315	valid-rmse:0.462927
[20]	train-rmse:0.342789	valid-rmse:0.390763
[30]	train-rmse:0.333623	valid-rmse:0.383752
[39]	train-rmse:0.329512	valid-rmse:0.381761
Iteration No: 516 ended. Search finished for the next optimal point.
Time taken: 36.6034
Function value obtained: 0.3818
Current minimum: 0.3801
Iteration No: 517 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 175, 'eta': 0.24220718646413794, 'colsample_bytree': 1.0, 'max_depth': 68, 'subsample': 1.0, 'lambda': 58.947638660304307, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.56031	valid-rmse:4.57861
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.480164	valid-rmse:0.520923
[20]	train-rmse:0.345738	valid-rmse:0.392964
[30]	train-rmse:0.335066	valid-rmse:0.384131
[39]	train-rmse:0.331035	valid-rmse:0.381438
Iteration No: 517 ended. Search finished for the next optimal point.
Time taken: 36.0535
Function value obtained: 0.3814
Current minimum: 0.3801
Iteration No: 518 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 140, 'eta': 0.185491612361112, 'colsample_bytree': 1.0, 'max_depth': 169, 'subsample': 1.0, 'lambda': 37.314563801950584, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89658	valid-rmse:4.91478
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.745832	valid-rmse:0.777408
[20]	train-rmse:0.362443	valid-rmse:0.40917
[30]	train-rmse:0.336886	valid-rmse:0.385898
[39]	train-rmse:0.331271	valid-rmse:0.382072
Iteration No: 518 ended. Search finished for the next optimal point.
Time taken: 35.7444
Function value obtained: 0.3821
Current minimum: 0.3801
Iteration No: 519 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 211, 'eta': 0.20081282622413027, 'colsample_bytree': 1.0, 'max_depth': 63, 'subsample': 1.0, 'lambda': 41.348602297202241, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.80562	valid-rmse:4.82384
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.646845	valid-rmse:0.680973
[20]	train-rmse:0.355924	valid-rmse:0.402482
[30]	train-rmse:0.338219	valid-rmse:0.386227
[39]	train-rmse:0.333373	valid-rmse:0.382619
Iteration No: 519 ended. Search finished for the next optimal point.
Time taken: 35.8154
Function value obtained: 0.3826
Current minimum: 0.3801
Iteration No: 520 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 114, 'eta': 0.23390486860428097, 'colsample_bytree': 1.0, 'max_depth': 167, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.61075	valid-rmse:4.62896
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.507744	valid-rmse:0.547165
[20]	train-rmse:0.347908	valid-rmse:0.395487
[30]	train-rmse:0.335258	valid-rmse:0.384878
[39]	train-rmse:0.330177	valid-rmse:0.381843
Iteration No: 520 ended. Search finished for the next optimal point.
Time taken: 36.3587
Function value obtained: 0.3818
Current minimum: 0.3801
Iteration No: 521 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 114, 'eta': 0.2577923096703586, 'colsample_bytree': 1.0, 'max_depth': 76, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.46904	valid-rmse:4.48729
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.446424	valid-rmse:0.488836
[20]	train-rmse:0.343981	valid-rmse:0.392448
[30]	train-rmse:0.333146	valid-rmse:0.383747
[39]	train-rmse:0.328741	valid-rmse:0.381366
Iteration No: 521 ended. Search finished for the next optimal point.
Time taken: 37.9323
Function value obtained: 0.3814
Current minimum: 0.3801
Iteration No: 522 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 132, 'eta': 0.17880223549788704, 'colsample_bytree': 0.70551622641393519, 'max_depth': 65, 'subsample': 1.0, 'lambda': 24.243008244417673, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.936	valid-rmse:4.95392
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.795423	valid-rmse:0.825496
[20]	train-rmse:0.365973	valid-rmse:0.41264
[30]	train-rmse:0.336183	valid-rmse:0.385365
[39]	train-rmse:0.330151	valid-rmse:0.381033
Iteration No: 522 ended. Search finished for the next optimal point.
Time taken: 32.0665
Function value obtained: 0.3810
Current minimum: 0.3801
Iteration No: 523 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 141, 'eta': 0.16587884140511952, 'colsample_bytree': 1.0, 'max_depth': 84, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00994	valid-rmse:5.02751
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.889903	valid-rmse:0.918004
[20]	train-rmse:0.364994	valid-rmse:0.413828
[30]	train-rmse:0.333355	valid-rmse:0.384888
[39]	train-rmse:0.329345	valid-rmse:0.382075
Iteration No: 523 ended. Search finished for the next optimal point.
Time taken: 43.3169
Function value obtained: 0.3821
Current minimum: 0.3801
Iteration No: 524 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 132, 'eta': 0.17909066395456077, 'colsample_bytree': 0.70439975123105469, 'max_depth': 65, 'subsample': 1.0, 'lambda': 24.349362978474417, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93429	valid-rmse:4.95221
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.793115	valid-rmse:0.823235
[20]	train-rmse:0.365602	valid-rmse:0.412263
[30]	train-rmse:0.336299	valid-rmse:0.38557
[39]	train-rmse:0.330144	valid-rmse:0.381053
Iteration No: 524 ended. Search finished for the next optimal point.
Time taken: 32.1825
Function value obtained: 0.3811
Current minimum: 0.3801
Iteration No: 525 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.17936020611338641, 'colsample_bytree': 0.70459161599199072, 'max_depth': 64, 'subsample': 1.0, 'lambda': 24.2701922969149, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93268	valid-rmse:4.9506
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.790717	valid-rmse:0.820741
[20]	train-rmse:0.365798	valid-rmse:0.41207
[30]	train-rmse:0.336347	valid-rmse:0.384946
[39]	train-rmse:0.329472	valid-rmse:0.3798
Iteration No: 525 ended. Search finished for the next optimal point.
Time taken: 30.9812
Function value obtained: 0.3798
Current minimum: 0.3798
Iteration No: 526 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.17921499281206149, 'colsample_bytree': 0.70422327936628815, 'max_depth': 64, 'subsample': 1.0, 'lambda': 24.230964371098764, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93354	valid-rmse:4.95147
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.791877	valid-rmse:0.821876
[20]	train-rmse:0.365902	valid-rmse:0.412295
[30]	train-rmse:0.336539	valid-rmse:0.385464
[39]	train-rmse:0.330365	valid-rmse:0.380938
Iteration No: 526 ended. Search finished for the next optimal point.
Time taken: 31.6201
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 527 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 174, 'eta': 0.21104008197400925, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 59.86573650866854, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.74558	valid-rmse:4.76377
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.59599	valid-rmse:0.631805
[20]	train-rmse:0.353834	valid-rmse:0.400623
[30]	train-rmse:0.337279	valid-rmse:0.385733
[39]	train-rmse:0.331921	valid-rmse:0.382201
Iteration No: 527 ended. Search finished for the next optimal point.
Time taken: 34.9971
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 528 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 298, 'eta': 0.14901873633858384, 'colsample_bytree': 0.94360645791072018, 'max_depth': 106, 'subsample': 0.99958693789946551, 'lambda': 86.305462237948902, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.11463	valid-rmse:5.13274
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.10617	valid-rmse:1.13235
[20]	train-rmse:0.430763	valid-rmse:0.47353
[30]	train-rmse:0.355307	valid-rmse:0.401639
[39]	train-rmse:0.342705	valid-rmse:0.389675
Iteration No: 528 ended. Search finished for the next optimal point.
Time taken: 29.7422
Function value obtained: 0.3897
Current minimum: 0.3798
Iteration No: 529 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 84, 'subsample': 1.0, 'lambda': 67.64992888799668, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21786	valid-rmse:4.23623
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.39229	valid-rmse:0.436034
[20]	train-rmse:0.343426	valid-rmse:0.389479
[30]	train-rmse:0.336154	valid-rmse:0.384057
[39]	train-rmse:0.332745	valid-rmse:0.381841
Iteration No: 529 ended. Search finished for the next optimal point.
Time taken: 38.5976
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 530 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 119, 'eta': 0.17312032661957116, 'colsample_bytree': 1.0, 'max_depth': 65, 'subsample': 1.0, 'lambda': 25.698115103142673, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96963	valid-rmse:4.98762
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.843331	valid-rmse:0.872699
[20]	train-rmse:0.371826	valid-rmse:0.418164
[30]	train-rmse:0.337003	valid-rmse:0.386074
[39]	train-rmse:0.330396	valid-rmse:0.381116
Iteration No: 530 ended. Search finished for the next optimal point.
Time taken: 36.3797
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 531 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 139, 'eta': 0.17902786427301506, 'colsample_bytree': 1.0, 'max_depth': 75, 'subsample': 1.0, 'lambda': 43.384485846499594, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93519	valid-rmse:4.95337
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.79688	valid-rmse:0.827364
[20]	train-rmse:0.369562	valid-rmse:0.415743
[30]	train-rmse:0.338395	valid-rmse:0.386832
[39]	train-rmse:0.331981	valid-rmse:0.381997
Iteration No: 531 ended. Search finished for the next optimal point.
Time taken: 36.5583
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 532 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 136, 'eta': 0.17744687592703823, 'colsample_bytree': 0.70549727358743874, 'max_depth': 67, 'subsample': 1.0, 'lambda': 23.399597653763596, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94403	valid-rmse:4.96195
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.80631	valid-rmse:0.836173
[20]	train-rmse:0.367541	valid-rmse:0.414
[30]	train-rmse:0.336737	valid-rmse:0.385825
[39]	train-rmse:0.330342	valid-rmse:0.38109
Iteration No: 532 ended. Search finished for the next optimal point.
Time taken: 32.7047
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 533 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 175, 'eta': 0.27366846694455527, 'colsample_bytree': 1.0, 'max_depth': 94, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.37492	valid-rmse:4.39328
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.421505	valid-rmse:0.464707
[20]	train-rmse:0.344202	valid-rmse:0.391257
[30]	train-rmse:0.334582	valid-rmse:0.383978
[39]	train-rmse:0.331038	valid-rmse:0.381951
Iteration No: 533 ended. Search finished for the next optimal point.
Time taken: 39.6754
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 534 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 285, 'eta': 0.29955700401802965, 'colsample_bytree': 0.51830812236506285, 'max_depth': 46, 'subsample': 0.80264078135502981, 'lambda': 1.6376727022324022, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21519	valid-rmse:4.23295
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.378521	valid-rmse:0.423274
[20]	train-rmse:0.345502	valid-rmse:0.391136
[30]	train-rmse:0.341066	valid-rmse:0.387305
[39]	train-rmse:0.339332	valid-rmse:0.385897
Iteration No: 534 ended. Search finished for the next optimal point.
Time taken: 30.6713
Function value obtained: 0.3859
Current minimum: 0.3798
Iteration No: 535 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 141, 'eta': 0.17921398595245069, 'colsample_bytree': 0.7004001701815854, 'max_depth': 65, 'subsample': 1.0, 'lambda': 22.453076981750328, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93347	valid-rmse:4.95139
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.791475	valid-rmse:0.821609
[20]	train-rmse:0.365649	valid-rmse:0.412155
[30]	train-rmse:0.336526	valid-rmse:0.385578
[39]	train-rmse:0.330258	valid-rmse:0.38089
Iteration No: 535 ended. Search finished for the next optimal point.
Time taken: 32.0788
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 536 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 173, 'eta': 0.23561892564173162, 'colsample_bytree': 1.0, 'max_depth': 82, 'subsample': 1.0, 'lambda': 71.962116370852357, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.59999	valid-rmse:4.61823
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.502243	valid-rmse:0.541884
[20]	train-rmse:0.347866	valid-rmse:0.394618
[30]	train-rmse:0.335651	valid-rmse:0.38444
[39]	train-rmse:0.330881	valid-rmse:0.381251
Iteration No: 536 ended. Search finished for the next optimal point.
Time taken: 37.5240
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 537 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 123, 'eta': 0.24130062935229904, 'colsample_bytree': 1.0, 'max_depth': 87, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.56687	valid-rmse:4.58509
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.486683	valid-rmse:0.526944
[20]	train-rmse:0.34663	valid-rmse:0.394337
[30]	train-rmse:0.334543	valid-rmse:0.384418
[39]	train-rmse:0.329835	valid-rmse:0.381462
Iteration No: 537 ended. Search finished for the next optimal point.
Time taken: 37.5884
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 538 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 15, 'eta': 0.29758509474121986, 'colsample_bytree': 0.40094806820100626, 'max_depth': 68, 'subsample': 0.84020587875165265, 'lambda': 89.956698418782864, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.23409	valid-rmse:4.25261
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.401337	valid-rmse:0.446288
[20]	train-rmse:0.347279	valid-rmse:0.395063
[30]	train-rmse:0.337837	valid-rmse:0.387134
[39]	train-rmse:0.334402	valid-rmse:0.384781
Iteration No: 538 ended. Search finished for the next optimal point.
Time taken: 30.4804
Function value obtained: 0.3848
Current minimum: 0.3798
Iteration No: 539 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 17, 'eta': 0.29961126895644563, 'colsample_bytree': 0.53766766148472811, 'max_depth': 44, 'subsample': 0.96899244771917448, 'lambda': 85.96883782627414, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22151	valid-rmse:4.24003
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.394812	valid-rmse:0.439602
[20]	train-rmse:0.346717	valid-rmse:0.393603
[30]	train-rmse:0.339711	valid-rmse:0.387654
[39]	train-rmse:0.336755	valid-rmse:0.3853
Iteration No: 539 ended. Search finished for the next optimal point.
Time taken: 33.5868
Function value obtained: 0.3853
Current minimum: 0.3798
Iteration No: 540 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 299, 'eta': 0.10651220906848112, 'colsample_bytree': 0.87064106360923854, 'max_depth': 76, 'subsample': 0.88161372960589379, 'lambda': 89.148255917647433, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.36754	valid-rmse:5.38566
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.79755	valid-rmse:1.81948
[20]	train-rmse:0.700549	valid-rmse:0.733692
[30]	train-rmse:0.422007	valid-rmse:0.465194
[39]	train-rmse:0.366526	valid-rmse:0.412109
Iteration No: 540 ended. Search finished for the next optimal point.
Time taken: 27.1376
Function value obtained: 0.4121
Current minimum: 0.3798
Iteration No: 541 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 139, 'eta': 0.27447349882721694, 'colsample_bytree': 1.0, 'max_depth': 74, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.37011	valid-rmse:4.3884
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.419414	valid-rmse:0.463012
[20]	train-rmse:0.342825	valid-rmse:0.390869
[30]	train-rmse:0.333275	valid-rmse:0.383573
[39]	train-rmse:0.329303	valid-rmse:0.381403
Iteration No: 541 ended. Search finished for the next optimal point.
Time taken: 39.3938
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 542 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.29990329889121192, 'colsample_bytree': 0.40620948299256893, 'max_depth': 149, 'subsample': 0.9987988201718615, 'lambda': 33.686971650381658, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21682	valid-rmse:4.23499
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.389989	valid-rmse:0.434958
[20]	train-rmse:0.346302	valid-rmse:0.393072
[30]	train-rmse:0.339285	valid-rmse:0.387056
[39]	train-rmse:0.336702	valid-rmse:0.38494
Iteration No: 542 ended. Search finished for the next optimal point.
Time taken: 28.7173
Function value obtained: 0.3849
Current minimum: 0.3798
Iteration No: 543 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.24274815969610922, 'colsample_bytree': 1.0, 'max_depth': 170, 'subsample': 1.0, 'lambda': 38.138516062433609, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55629	valid-rmse:4.57459
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.476062	valid-rmse:0.516667
[20]	train-rmse:0.346463	valid-rmse:0.392672
[30]	train-rmse:0.336688	valid-rmse:0.384378
[39]	train-rmse:0.332913	valid-rmse:0.381752
Iteration No: 543 ended. Search finished for the next optimal point.
Time taken: 38.1240
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 544 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.17649327739838683, 'colsample_bytree': 0.72156467496076515, 'max_depth': 68, 'subsample': 1.0, 'lambda': 24.310024267415464, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94973	valid-rmse:4.96765
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.814444	valid-rmse:0.84417
[20]	train-rmse:0.369067	valid-rmse:0.414954
[30]	train-rmse:0.337298	valid-rmse:0.385697
[39]	train-rmse:0.330961	valid-rmse:0.381048
Iteration No: 544 ended. Search finished for the next optimal point.
Time taken: 33.8867
Function value obtained: 0.3810
Current minimum: 0.3798
Iteration No: 545 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 113, 'eta': 0.17857131512401583, 'colsample_bytree': 1.0, 'max_depth': 56, 'subsample': 1.0, 'lambda': 31.654003432560074, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93745	valid-rmse:4.95543
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.798061	valid-rmse:0.828697
[20]	train-rmse:0.366673	valid-rmse:0.413878
[30]	train-rmse:0.336374	valid-rmse:0.386137
[39]	train-rmse:0.330291	valid-rmse:0.381856
Iteration No: 545 ended. Search finished for the next optimal point.
Time taken: 38.3292
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 546 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 210, 'eta': 0.18972596081177237, 'colsample_bytree': 1.0, 'max_depth': 54, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86771	valid-rmse:4.88526
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.691811	valid-rmse:0.724003
[20]	train-rmse:0.348667	valid-rmse:0.397401
[30]	train-rmse:0.334559	valid-rmse:0.384595
[39]	train-rmse:0.331835	valid-rmse:0.382692
Iteration No: 546 ended. Search finished for the next optimal point.
Time taken: 43.7759
Function value obtained: 0.3827
Current minimum: 0.3798
Iteration No: 547 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 139, 'eta': 0.17660107369991623, 'colsample_bytree': 0.71848710437268282, 'max_depth': 68, 'subsample': 1.0, 'lambda': 24.120056655292302, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94908	valid-rmse:4.967
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.813505	valid-rmse:0.843194
[20]	train-rmse:0.368501	valid-rmse:0.414619
[30]	train-rmse:0.337501	valid-rmse:0.386396
[39]	train-rmse:0.331072	valid-rmse:0.381516
Iteration No: 547 ended. Search finished for the next optimal point.
Time taken: 34.3302
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 548 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 172, 'subsample': 1.0, 'lambda': 43.70238737312723, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21655	valid-rmse:4.235
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.387522	valid-rmse:0.432023
[20]	train-rmse:0.342347	valid-rmse:0.389016
[30]	train-rmse:0.335271	valid-rmse:0.384092
[39]	train-rmse:0.332274	valid-rmse:0.382243
Iteration No: 548 ended. Search finished for the next optimal point.
Time taken: 42.2067
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 549 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 125, 'eta': 0.24177955050431649, 'colsample_bytree': 1.0, 'max_depth': 87, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.56403	valid-rmse:4.58225
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.485443	valid-rmse:0.525758
[20]	train-rmse:0.346667	valid-rmse:0.394147
[30]	train-rmse:0.334608	valid-rmse:0.38432
[39]	train-rmse:0.329812	valid-rmse:0.381371
Iteration No: 549 ended. Search finished for the next optimal point.
Time taken: 39.8114
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 550 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 299, 'eta': 0.2987767422483103, 'colsample_bytree': 0.85198996246801773, 'max_depth': 38, 'subsample': 0.88422090696085198, 'lambda': 77.510227859528285, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22644	valid-rmse:4.24493
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.396038	valid-rmse:0.439981
[20]	train-rmse:0.345824	valid-rmse:0.391527
[30]	train-rmse:0.337582	valid-rmse:0.385216
[39]	train-rmse:0.334143	valid-rmse:0.382854
Iteration No: 550 ended. Search finished for the next optimal point.
Time taken: 35.7824
Function value obtained: 0.3829
Current minimum: 0.3798
Iteration No: 551 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 0.40000000000000002, 'max_depth': 63, 'subsample': 1.0, 'lambda': 58.802692801944652, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21784	valid-rmse:4.23625
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.401217	valid-rmse:0.444538
[20]	train-rmse:0.349593	valid-rmse:0.395659
[30]	train-rmse:0.339036	valid-rmse:0.386873
[39]	train-rmse:0.334882	valid-rmse:0.384189
Iteration No: 551 ended. Search finished for the next optimal point.
Time taken: 28.7405
Function value obtained: 0.3842
Current minimum: 0.3798
Iteration No: 552 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 28, 'eta': 0.17650017933373918, 'colsample_bytree': 0.43773182278025724, 'max_depth': 145, 'subsample': 0.97815151212808371, 'lambda': 89.685990744676332, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95177	valid-rmse:4.97
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.827184	valid-rmse:0.858049
[20]	train-rmse:0.381337	valid-rmse:0.427975
[30]	train-rmse:0.34151	valid-rmse:0.391824
[39]	train-rmse:0.331915	valid-rmse:0.384425
Iteration No: 552 ended. Search finished for the next optimal point.
Time taken: 31.0598
Function value obtained: 0.3844
Current minimum: 0.3798
Iteration No: 553 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.17395580920148579, 'colsample_bytree': 1.0, 'max_depth': 134, 'subsample': 1.0, 'lambda': 27.573835875698663, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96475	valid-rmse:4.98273
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.836042	valid-rmse:0.865527
[20]	train-rmse:0.371418	valid-rmse:0.417824
[30]	train-rmse:0.337864	valid-rmse:0.386701
[39]	train-rmse:0.331074	valid-rmse:0.381489
Iteration No: 553 ended. Search finished for the next optimal point.
Time taken: 36.4577
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 554 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 135, 'eta': 0.17370380513256511, 'colsample_bytree': 1.0, 'max_depth': 134, 'subsample': 1.0, 'lambda': 26.906213659742114, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96622	valid-rmse:4.9842
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.838068	valid-rmse:0.867473
[20]	train-rmse:0.372017	valid-rmse:0.418225
[30]	train-rmse:0.3381	valid-rmse:0.38677
[39]	train-rmse:0.331405	valid-rmse:0.381771
Iteration No: 554 ended. Search finished for the next optimal point.
Time taken: 38.7014
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 555 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 215, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 84, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21883	valid-rmse:4.2372
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.392183	valid-rmse:0.436621
[20]	train-rmse:0.343262	valid-rmse:0.390464
[30]	train-rmse:0.334879	valid-rmse:0.384384
[39]	train-rmse:0.331577	valid-rmse:0.382589
Iteration No: 555 ended. Search finished for the next optimal point.
Time taken: 39.6212
Function value obtained: 0.3826
Current minimum: 0.3798
Iteration No: 556 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 290, 'eta': 0.24933274934075542, 'colsample_bytree': 0.89407814365952931, 'max_depth': 154, 'subsample': 0.81590745093774109, 'lambda': 0.81703747312211494, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.51365	valid-rmse:4.53138
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.439436	valid-rmse:0.48141
[20]	train-rmse:0.340898	valid-rmse:0.388142
[30]	train-rmse:0.335509	valid-rmse:0.383606
[39]	train-rmse:0.333198	valid-rmse:0.382283
Iteration No: 556 ended. Search finished for the next optimal point.
Time taken: 39.8908
Function value obtained: 0.3823
Current minimum: 0.3798
Iteration No: 557 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 106, 'eta': 0.21969826716517832, 'colsample_bytree': 1.0, 'max_depth': 168, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.69505	valid-rmse:4.71324
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.56042	valid-rmse:0.597927
[20]	train-rmse:0.351766	valid-rmse:0.399517
[30]	train-rmse:0.336427	valid-rmse:0.38618
[39]	train-rmse:0.330458	valid-rmse:0.38187
Iteration No: 557 ended. Search finished for the next optimal point.
Time taken: 39.4236
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 558 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.24246653262305207, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 38.841828057912238, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55799	valid-rmse:4.57629
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.476717	valid-rmse:0.516937
[20]	train-rmse:0.34683	valid-rmse:0.392922
[30]	train-rmse:0.336817	valid-rmse:0.384562
[39]	train-rmse:0.333	valid-rmse:0.381931
Iteration No: 558 ended. Search finished for the next optimal point.
Time taken: 39.0970
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 559 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 162, 'eta': 0.18532285927798359, 'colsample_bytree': 0.70528461529584519, 'max_depth': 61, 'subsample': 1.0, 'lambda': 20.523850644995225, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89705	valid-rmse:4.91499
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.744234	valid-rmse:0.775488
[20]	train-rmse:0.360439	valid-rmse:0.406727
[30]	train-rmse:0.336214	valid-rmse:0.384482
[39]	train-rmse:0.330827	valid-rmse:0.380756
Iteration No: 559 ended. Search finished for the next optimal point.
Time taken: 35.3011
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 560 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 162, 'eta': 0.18522952363530953, 'colsample_bytree': 0.70610942014222355, 'max_depth': 61, 'subsample': 1.0, 'lambda': 20.667316791448126, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89762	valid-rmse:4.91555
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.744952	valid-rmse:0.776198
[20]	train-rmse:0.360436	valid-rmse:0.40685
[30]	train-rmse:0.336299	valid-rmse:0.384797
[39]	train-rmse:0.330928	valid-rmse:0.381091
Iteration No: 560 ended. Search finished for the next optimal point.
Time taken: 36.9932
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 561 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 159, 'eta': 0.18444045836738429, 'colsample_bytree': 0.70671005485786131, 'max_depth': 61, 'subsample': 1.0, 'lambda': 21.064336373994138, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90233	valid-rmse:4.92026
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.750416	valid-rmse:0.781461
[20]	train-rmse:0.361142	valid-rmse:0.407646
[30]	train-rmse:0.336436	valid-rmse:0.385149
[39]	train-rmse:0.330844	valid-rmse:0.381075
Iteration No: 561 ended. Search finished for the next optimal point.
Time taken: 37.4248
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 562 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 162, 'eta': 0.17874532626841461, 'colsample_bytree': 0.60789387003767836, 'max_depth': 68, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93404	valid-rmse:4.95158
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.775834	valid-rmse:0.806298
[20]	train-rmse:0.354628	valid-rmse:0.403243
[30]	train-rmse:0.334345	valid-rmse:0.384771
[39]	train-rmse:0.330666	valid-rmse:0.382223
Iteration No: 562 ended. Search finished for the next optimal point.
Time taken: 37.0190
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 563 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 127, 'eta': 0.17590747629417439, 'colsample_bytree': 0.73712269977069766, 'max_depth': 69, 'subsample': 1.0, 'lambda': 27.480787876517901, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95334	valid-rmse:4.97124
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.820014	valid-rmse:0.849852
[20]	train-rmse:0.3703	valid-rmse:0.41661
[30]	train-rmse:0.338009	valid-rmse:0.38701
[39]	train-rmse:0.330675	valid-rmse:0.381464
Iteration No: 563 ended. Search finished for the next optimal point.
Time taken: 34.8076
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 564 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 222, 'eta': 0.1975085487468643, 'colsample_bytree': 1.0, 'max_depth': 63, 'subsample': 1.0, 'lambda': 39.10700125873786, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.82519	valid-rmse:4.8434
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.666129	valid-rmse:0.69997
[20]	train-rmse:0.357345	valid-rmse:0.403968
[30]	train-rmse:0.338311	valid-rmse:0.386232
[39]	train-rmse:0.332633	valid-rmse:0.381926
Iteration No: 564 ended. Search finished for the next optimal point.
Time taken: 37.0506
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 565 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.18695070158523758, 'colsample_bytree': 1.0, 'max_depth': 68, 'subsample': 1.0, 'lambda': 52.414757646584597, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88835	valid-rmse:4.90655
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.737518	valid-rmse:0.769513
[20]	train-rmse:0.363864	valid-rmse:0.410625
[30]	train-rmse:0.338274	valid-rmse:0.38685
[39]	train-rmse:0.331742	valid-rmse:0.382045
Iteration No: 565 ended. Search finished for the next optimal point.
Time taken: 38.9199
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 566 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 137, 'eta': 0.27615229978006584, 'colsample_bytree': 1.0, 'max_depth': 172, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.36016	valid-rmse:4.37845
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.417611	valid-rmse:0.461075
[20]	train-rmse:0.342939	valid-rmse:0.390739
[30]	train-rmse:0.333032	valid-rmse:0.383351
[39]	train-rmse:0.329439	valid-rmse:0.381577
Iteration No: 566 ended. Search finished for the next optimal point.
Time taken: 40.9922
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 567 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.27591920376610468, 'colsample_bytree': 1.0, 'max_depth': 172, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.36154	valid-rmse:4.37983
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.417448	valid-rmse:0.460975
[20]	train-rmse:0.342606	valid-rmse:0.390485
[30]	train-rmse:0.333147	valid-rmse:0.383348
[39]	train-rmse:0.329701	valid-rmse:0.381785
Iteration No: 567 ended. Search finished for the next optimal point.
Time taken: 41.2369
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 568 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 217, 'eta': 0.22462737851677522, 'colsample_bytree': 1.0, 'max_depth': 163, 'subsample': 1.0, 'lambda': 52.655556988554366, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.66448	valid-rmse:4.68274
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.536745	valid-rmse:0.574785
[20]	train-rmse:0.349236	valid-rmse:0.395958
[30]	train-rmse:0.33664	valid-rmse:0.384886
[39]	train-rmse:0.332067	valid-rmse:0.381904
Iteration No: 568 ended. Search finished for the next optimal point.
Time taken: 39.1023
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 569 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 120, 'eta': 0.26359458485902093, 'colsample_bytree': 1.0, 'max_depth': 72, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.43462	valid-rmse:4.45289
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.436336	valid-rmse:0.479295
[20]	train-rmse:0.34365	valid-rmse:0.392048
[30]	train-rmse:0.332998	valid-rmse:0.383628
[39]	train-rmse:0.328746	valid-rmse:0.381163
Iteration No: 569 ended. Search finished for the next optimal point.
Time taken: 41.5434
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 570 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 16, 'eta': 0.15807035236539915, 'colsample_bytree': 0.78485815642242307, 'max_depth': 63, 'subsample': 0.94753805152478787, 'lambda': 1.8139938085875833, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.05759	valid-rmse:5.07538
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.978218	valid-rmse:1.00557
[20]	train-rmse:0.382976	valid-rmse:0.431941
[30]	train-rmse:0.339012	valid-rmse:0.391049
[39]	train-rmse:0.334044	valid-rmse:0.386743
Iteration No: 570 ended. Search finished for the next optimal point.
Time taken: 42.0662
Function value obtained: 0.3867
Current minimum: 0.3798
Iteration No: 571 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 185, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 74, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21882	valid-rmse:4.23724
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391812	valid-rmse:0.436398
[20]	train-rmse:0.342257	valid-rmse:0.390022
[30]	train-rmse:0.333858	valid-rmse:0.384091
[39]	train-rmse:0.33063	valid-rmse:0.382272
Iteration No: 571 ended. Search finished for the next optimal point.
Time taken: 42.9671
Function value obtained: 0.3823
Current minimum: 0.3798
Iteration No: 572 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26629142058634259, 'colsample_bytree': 1.0, 'max_depth': 64, 'subsample': 1.0, 'lambda': 38.96482146050559, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41647	valid-rmse:4.43482
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.426197	valid-rmse:0.469172
[20]	train-rmse:0.344373	valid-rmse:0.390977
[30]	train-rmse:0.335973	valid-rmse:0.384219
[39]	train-rmse:0.332157	valid-rmse:0.381851
Iteration No: 572 ended. Search finished for the next optimal point.
Time taken: 44.1912
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 573 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 145, 'eta': 0.18077537457617249, 'colsample_bytree': 1.0, 'max_depth': 171, 'subsample': 1.0, 'lambda': 31.687521134946259, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92437	valid-rmse:4.94235
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.780557	valid-rmse:0.811231
[20]	train-rmse:0.365659	valid-rmse:0.411876
[30]	train-rmse:0.337582	valid-rmse:0.386078
[39]	train-rmse:0.331244	valid-rmse:0.381367
Iteration No: 573 ended. Search finished for the next optimal point.
Time taken: 39.7470
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 574 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26709226798362695, 'colsample_bytree': 1.0, 'max_depth': 171, 'subsample': 1.0, 'lambda': 38.878892703937652, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41171	valid-rmse:4.43007
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.4245	valid-rmse:0.467574
[20]	train-rmse:0.34401	valid-rmse:0.390836
[30]	train-rmse:0.33599	valid-rmse:0.384334
[39]	train-rmse:0.332261	valid-rmse:0.381938
Iteration No: 574 ended. Search finished for the next optimal point.
Time taken: 41.1416
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 575 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 26, 'eta': 0.24140965042701559, 'colsample_bytree': 0.7501298963291918, 'max_depth': 46, 'subsample': 0.8432346527018143, 'lambda': 88.972910551936025, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.56698	valid-rmse:4.58532
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.487784	valid-rmse:0.528606
[20]	train-rmse:0.352366	valid-rmse:0.399448
[30]	train-rmse:0.342843	valid-rmse:0.390184
[39]	train-rmse:0.338718	valid-rmse:0.386929
Iteration No: 575 ended. Search finished for the next optimal point.
Time taken: 36.6980
Function value obtained: 0.3869
Current minimum: 0.3798
Iteration No: 576 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 163, 'eta': 0.1629277668435159, 'colsample_bytree': 1.0, 'max_depth': 124, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02761	valid-rmse:5.04519
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.919892	valid-rmse:0.947474
[20]	train-rmse:0.37008	valid-rmse:0.418118
[30]	train-rmse:0.334199	valid-rmse:0.385246
[39]	train-rmse:0.330026	valid-rmse:0.38212
Iteration No: 576 ended. Search finished for the next optimal point.
Time taken: 44.5463
Function value obtained: 0.3821
Current minimum: 0.3798
Iteration No: 577 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 184, 'eta': 0.26155112883693932, 'colsample_bytree': 0.7191534547843792, 'max_depth': 81, 'subsample': 1.0, 'lambda': 62.565996659023746, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.44598	valid-rmse:4.46423
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.438348	valid-rmse:0.48038
[20]	train-rmse:0.344279	valid-rmse:0.391082
[30]	train-rmse:0.334569	valid-rmse:0.383442
[39]	train-rmse:0.330613	valid-rmse:0.381373
Iteration No: 577 ended. Search finished for the next optimal point.
Time taken: 36.5138
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 578 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 289, 'eta': 0.14285392882336889, 'colsample_bytree': 0.40030326865882893, 'max_depth': 198, 'subsample': 0.80016162587898021, 'lambda': 0.97062223526072, 'gamma': 1, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.14872	valid-rmse:5.1666
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:1.1678	valid-rmse:1.19215
[20]	train-rmse:0.433274	valid-rmse:0.475428
[30]	train-rmse:0.352627	valid-rmse:0.398816
[39]	train-rmse:0.343246	valid-rmse:0.389608
Iteration No: 578 ended. Search finished for the next optimal point.
Time taken: 30.9137
Function value obtained: 0.3896
Current minimum: 0.3798
Iteration No: 579 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 120, 'eta': 0.17552928267312873, 'colsample_bytree': 0.71192732664842151, 'max_depth': 69, 'subsample': 1.0, 'lambda': 25.43803462244782, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95552	valid-rmse:4.97344
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.822912	valid-rmse:0.852629
[20]	train-rmse:0.36961	valid-rmse:0.416088
[30]	train-rmse:0.33696	valid-rmse:0.386052
[39]	train-rmse:0.329597	valid-rmse:0.380622
Iteration No: 579 ended. Search finished for the next optimal point.
Time taken: 35.1779
Function value obtained: 0.3806
Current minimum: 0.3798
Iteration No: 580 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 33, 'eta': 0.18232567276902539, 'colsample_bytree': 0.40138809977082557, 'max_depth': 153, 'subsample': 0.87068459593080649, 'lambda': 1.7187773888002711, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91358	valid-rmse:4.9314
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.756799	valid-rmse:0.788169
[20]	train-rmse:0.353537	valid-rmse:0.406286
[30]	train-rmse:0.329898	valid-rmse:0.387257
[39]	train-rmse:0.325641	valid-rmse:0.385535
Iteration No: 580 ended. Search finished for the next optimal point.
Time taken: 35.7384
Function value obtained: 0.3855
Current minimum: 0.3798
Iteration No: 581 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 123, 'eta': 0.17453897060295701, 'colsample_bytree': 0.7206890040381928, 'max_depth': 71, 'subsample': 1.0, 'lambda': 25.076878093712267, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9614	valid-rmse:4.97932
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.83156	valid-rmse:0.861259
[20]	train-rmse:0.370872	valid-rmse:0.41742
[30]	train-rmse:0.3369	valid-rmse:0.386286
[39]	train-rmse:0.330026	valid-rmse:0.381217
Iteration No: 581 ended. Search finished for the next optimal point.
Time taken: 36.2547
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 582 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.27125246318615248, 'colsample_bytree': 0.7435032349015549, 'max_depth': 77, 'subsample': 1.0, 'lambda': 39.631640031938176, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.3873	valid-rmse:4.40561
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.419585	valid-rmse:0.462498
[20]	train-rmse:0.344721	valid-rmse:0.391117
[30]	train-rmse:0.33604	valid-rmse:0.384272
[39]	train-rmse:0.332747	valid-rmse:0.382195
Iteration No: 582 ended. Search finished for the next optimal point.
Time taken: 37.0432
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 583 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 200, 'eta': 0.2078117410464298, 'colsample_bytree': 1.0, 'max_depth': 167, 'subsample': 1.0, 'lambda': 46.656391819885144, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.76419	valid-rmse:4.78242
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.609159	valid-rmse:0.644302
[20]	train-rmse:0.352793	valid-rmse:0.39925
[30]	train-rmse:0.337023	valid-rmse:0.385052
[39]	train-rmse:0.332139	valid-rmse:0.381576
Iteration No: 583 ended. Search finished for the next optimal point.
Time taken: 39.2767
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 584 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 113, 'eta': 0.2613569942179117, 'colsample_bytree': 1.0, 'max_depth': 74, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4479	valid-rmse:4.46616
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.44115	valid-rmse:0.483819
[20]	train-rmse:0.343691	valid-rmse:0.391822
[30]	train-rmse:0.333409	valid-rmse:0.383777
[39]	train-rmse:0.328955	valid-rmse:0.38125
Iteration No: 584 ended. Search finished for the next optimal point.
Time taken: 41.1275
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 585 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 137, 'eta': 0.27609208992817369, 'colsample_bytree': 1.0, 'max_depth': 172, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.36051	valid-rmse:4.37881
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.417704	valid-rmse:0.46117
[20]	train-rmse:0.343523	valid-rmse:0.391251
[30]	train-rmse:0.333668	valid-rmse:0.383956
[39]	train-rmse:0.329686	valid-rmse:0.382085
Iteration No: 585 ended. Search finished for the next optimal point.
Time taken: 42.9348
Function value obtained: 0.3821
Current minimum: 0.3798
Iteration No: 586 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 150, 'eta': 0.16237841898400857, 'colsample_bytree': 1.0, 'max_depth': 102, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.03213	valid-rmse:5.04972
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.926068	valid-rmse:0.953353
[20]	train-rmse:0.371024	valid-rmse:0.419196
[30]	train-rmse:0.334816	valid-rmse:0.385935
[39]	train-rmse:0.330431	valid-rmse:0.382666
Iteration No: 586 ended. Search finished for the next optimal point.
Time taken: 46.2135
Function value obtained: 0.3827
Current minimum: 0.3798
Iteration No: 587 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 124, 'eta': 0.17698597136976185, 'colsample_bytree': 0.70559691407616565, 'max_depth': 67, 'subsample': 1.0, 'lambda': 25.443367516805491, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94686	valid-rmse:4.96478
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.810638	valid-rmse:0.84064
[20]	train-rmse:0.36784	valid-rmse:0.414586
[30]	train-rmse:0.33672	valid-rmse:0.385995
[39]	train-rmse:0.330011	valid-rmse:0.38097
Iteration No: 587 ended. Search finished for the next optimal point.
Time taken: 36.6826
Function value obtained: 0.3810
Current minimum: 0.3798
Iteration No: 588 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 159, 'eta': 0.18716564740431033, 'colsample_bytree': 0.70694794896008328, 'max_depth': 60, 'subsample': 1.0, 'lambda': 21.513601167498987, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88614	valid-rmse:4.90407
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.730898	valid-rmse:0.762548
[20]	train-rmse:0.359387	valid-rmse:0.405983
[30]	train-rmse:0.336028	valid-rmse:0.384656
[39]	train-rmse:0.330599	valid-rmse:0.380759
Iteration No: 588 ended. Search finished for the next optimal point.
Time taken: 36.8024
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 589 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.20196555556915324, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 56.628625966467851, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.79925	valid-rmse:4.81747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.643253	valid-rmse:0.677567
[20]	train-rmse:0.35613	valid-rmse:0.402728
[30]	train-rmse:0.337265	valid-rmse:0.385626
[39]	train-rmse:0.331701	valid-rmse:0.381713
Iteration No: 589 ended. Search finished for the next optimal point.
Time taken: 39.9520
Function value obtained: 0.3817
Current minimum: 0.3798
Iteration No: 590 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 144, 'eta': 0.18301015987653241, 'colsample_bytree': 0.74292927472771186, 'max_depth': 64, 'subsample': 0.80000000000000004, 'lambda': 26.169889658111806, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91132	valid-rmse:4.92934
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.764434	valid-rmse:0.795251
[20]	train-rmse:0.365519	valid-rmse:0.411828
[30]	train-rmse:0.338624	valid-rmse:0.386899
[39]	train-rmse:0.333144	valid-rmse:0.382862
Iteration No: 590 ended. Search finished for the next optimal point.
Time taken: 35.8486
Function value obtained: 0.3829
Current minimum: 0.3798
Iteration No: 591 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26607298033633164, 'colsample_bytree': 1.0, 'max_depth': 80, 'subsample': 1.0, 'lambda': 56.273983463427449, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4185	valid-rmse:4.43685
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.429311	valid-rmse:0.472053
[20]	train-rmse:0.344904	valid-rmse:0.391127
[30]	train-rmse:0.336237	valid-rmse:0.383887
[39]	train-rmse:0.33276	valid-rmse:0.381568
Iteration No: 591 ended. Search finished for the next optimal point.
Time taken: 41.7417
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 592 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 174, 'eta': 0.25817810727666546, 'colsample_bytree': 0.73228807427598519, 'max_depth': 82, 'subsample': 1.0, 'lambda': 64.199104148509491, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.46605	valid-rmse:4.4843
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.444456	valid-rmse:0.48633
[20]	train-rmse:0.344681	valid-rmse:0.391572
[30]	train-rmse:0.334316	valid-rmse:0.383342
[39]	train-rmse:0.33059	valid-rmse:0.381366
Iteration No: 592 ended. Search finished for the next optimal point.
Time taken: 39.2307
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 593 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 122, 'eta': 0.17393800774217905, 'colsample_bytree': 0.72209624802300054, 'max_depth': 72, 'subsample': 1.0, 'lambda': 24.867182854706101, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96496	valid-rmse:4.98288
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.836541	valid-rmse:0.866126
[20]	train-rmse:0.371472	valid-rmse:0.417875
[30]	train-rmse:0.3374	valid-rmse:0.386229
[39]	train-rmse:0.3304	valid-rmse:0.381086
Iteration No: 593 ended. Search finished for the next optimal point.
Time taken: 38.3115
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 594 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.1774816380810201, 'colsample_bytree': 0.58979218578928183, 'max_depth': 69, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94092	valid-rmse:4.95843
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.784521	valid-rmse:0.814547
[20]	train-rmse:0.353386	valid-rmse:0.402092
[30]	train-rmse:0.331935	valid-rmse:0.382586
[39]	train-rmse:0.328464	valid-rmse:0.380344
Iteration No: 594 ended. Search finished for the next optimal point.
Time taken: 39.2763
Function value obtained: 0.3803
Current minimum: 0.3798
Iteration No: 595 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 296, 'eta': 0.29822276232506917, 'colsample_bytree': 0.99480375205715799, 'max_depth': 50, 'subsample': 0.90339661698207474, 'lambda': 86.698574604006112, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22954	valid-rmse:4.2479
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.397512	valid-rmse:0.441261
[20]	train-rmse:0.349154	valid-rmse:0.394338
[30]	train-rmse:0.34287	valid-rmse:0.388848
[39]	train-rmse:0.339342	valid-rmse:0.385793
Iteration No: 595 ended. Search finished for the next optimal point.
Time taken: 39.2732
Function value obtained: 0.3858
Current minimum: 0.3798
Iteration No: 596 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 126, 'eta': 0.17421700751964742, 'colsample_bytree': 0.70999112568041811, 'max_depth': 72, 'subsample': 1.0, 'lambda': 23.030923558080161, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96323	valid-rmse:4.98115
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.833761	valid-rmse:0.863165
[20]	train-rmse:0.370302	valid-rmse:0.416523
[30]	train-rmse:0.336689	valid-rmse:0.385582
[39]	train-rmse:0.330033	valid-rmse:0.380602
Iteration No: 596 ended. Search finished for the next optimal point.
Time taken: 37.6230
Function value obtained: 0.3806
Current minimum: 0.3798
Iteration No: 597 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.17754609276865024, 'colsample_bytree': 0.59296555584138355, 'max_depth': 69, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94054	valid-rmse:4.95805
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.784387	valid-rmse:0.814282
[20]	train-rmse:0.35361	valid-rmse:0.402205
[30]	train-rmse:0.332209	valid-rmse:0.382608
[39]	train-rmse:0.328543	valid-rmse:0.380236
Iteration No: 597 ended. Search finished for the next optimal point.
Time taken: 39.7973
Function value obtained: 0.3802
Current minimum: 0.3798
Iteration No: 598 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 109, 'eta': 0.26013943446498722, 'colsample_bytree': 1.0, 'max_depth': 75, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.45512	valid-rmse:4.47338
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.443309	valid-rmse:0.485988
[20]	train-rmse:0.343343	valid-rmse:0.391592
[30]	train-rmse:0.333027	valid-rmse:0.38368
[39]	train-rmse:0.328749	valid-rmse:0.381567
Iteration No: 598 ended. Search finished for the next optimal point.
Time taken: 44.2576
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 599 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 147, 'eta': 0.17840174140600981, 'colsample_bytree': 1.0, 'max_depth': 173, 'subsample': 1.0, 'lambda': 29.632977358864274, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93841	valid-rmse:4.95639
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.799307	valid-rmse:0.829483
[20]	train-rmse:0.367769	valid-rmse:0.414036
[30]	train-rmse:0.338133	valid-rmse:0.38658
[39]	train-rmse:0.331655	valid-rmse:0.381882
Iteration No: 599 ended. Search finished for the next optimal point.
Time taken: 41.2137
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 600 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 178, 'eta': 0.16878548110353708, 'colsample_bytree': 1.0, 'max_depth': 166, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99267	valid-rmse:5.0102
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.862484	valid-rmse:0.890879
[20]	train-rmse:0.363033	valid-rmse:0.411244
[30]	train-rmse:0.334582	valid-rmse:0.385241
[39]	train-rmse:0.330226	valid-rmse:0.381988
Iteration No: 600 ended. Search finished for the next optimal point.
Time taken: 47.8674
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 601 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.16479843579552511, 'colsample_bytree': 1.0, 'max_depth': 87, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01642	valid-rmse:5.03404
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.900245	valid-rmse:0.927893
[20]	train-rmse:0.36659	valid-rmse:0.4153
[30]	train-rmse:0.333866	valid-rmse:0.385511
[39]	train-rmse:0.329388	valid-rmse:0.382136
Iteration No: 601 ended. Search finished for the next optimal point.
Time taken: 48.4423
Function value obtained: 0.3821
Current minimum: 0.3798
Iteration No: 602 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 158, 'eta': 0.19173021010820224, 'colsample_bytree': 0.40000000000000002, 'max_depth': 50, 'subsample': 1.0, 'lambda': 31.570382739256388, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85951	valid-rmse:4.8774
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.707846	valid-rmse:0.740353
[20]	train-rmse:0.365212	valid-rmse:0.411034
[30]	train-rmse:0.34014	valid-rmse:0.38803
[39]	train-rmse:0.333329	valid-rmse:0.382736
Iteration No: 602 ended. Search finished for the next optimal point.
Time taken: 32.9508
Function value obtained: 0.3827
Current minimum: 0.3798
Iteration No: 603 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 192, 'eta': 0.2457040103428664, 'colsample_bytree': 0.40000000000000002, 'max_depth': 67, 'subsample': 1.0, 'lambda': 59.07670303731814, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.53997	valid-rmse:4.55825
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.480349	valid-rmse:0.52081
[20]	train-rmse:0.353054	valid-rmse:0.399247
[30]	train-rmse:0.338983	valid-rmse:0.387158
[39]	train-rmse:0.333477	valid-rmse:0.383321
Iteration No: 603 ended. Search finished for the next optimal point.
Time taken: 33.3621
Function value obtained: 0.3833
Current minimum: 0.3798
Iteration No: 604 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 213, 'eta': 0.23324154313004561, 'colsample_bytree': 1.0, 'max_depth': 165, 'subsample': 1.0, 'lambda': 58.439501854282597, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.61353	valid-rmse:4.63181
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.506986	valid-rmse:0.546186
[20]	train-rmse:0.348462	valid-rmse:0.395523
[30]	train-rmse:0.336633	valid-rmse:0.385485
[39]	train-rmse:0.332306	valid-rmse:0.382656
Iteration No: 604 ended. Search finished for the next optimal point.
Time taken: 42.3102
Function value obtained: 0.3827
Current minimum: 0.3798
Iteration No: 605 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 90, 'eta': 0.17925784128783767, 'colsample_bytree': 1.0, 'max_depth': 57, 'subsample': 1.0, 'lambda': 34.269889009193221, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93351	valid-rmse:4.95167
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.793608	valid-rmse:0.824568
[20]	train-rmse:0.36637	valid-rmse:0.414068
[30]	train-rmse:0.335571	valid-rmse:0.386386
[39]	train-rmse:0.328848	valid-rmse:0.382008
Iteration No: 605 ended. Search finished for the next optimal point.
Time taken: 42.0107
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 606 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 192, 'eta': 0.18473317853403992, 'colsample_bytree': 1.0, 'max_depth': 57, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89749	valid-rmse:4.91502
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.727071	valid-rmse:0.75859
[20]	train-rmse:0.349941	valid-rmse:0.398687
[30]	train-rmse:0.333728	valid-rmse:0.383993
[39]	train-rmse:0.330667	valid-rmse:0.382074
Iteration No: 606 ended. Search finished for the next optimal point.
Time taken: 47.0698
Function value obtained: 0.3821
Current minimum: 0.3798
Iteration No: 607 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 113, 'eta': 0.17213853670105245, 'colsample_bytree': 0.40000000000000002, 'max_depth': 75, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97301	valid-rmse:4.99057
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.834564	valid-rmse:0.863646
[20]	train-rmse:0.361703	valid-rmse:0.410849
[30]	train-rmse:0.334081	valid-rmse:0.385823
[39]	train-rmse:0.329085	valid-rmse:0.382217
Iteration No: 607 ended. Search finished for the next optimal point.
Time taken: 36.3074
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 608 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 181, 'eta': 0.27155387482128934, 'colsample_bytree': 1.0, 'max_depth': 90, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.38746	valid-rmse:4.40581
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.423671	valid-rmse:0.467021
[20]	train-rmse:0.344645	valid-rmse:0.391677
[30]	train-rmse:0.334745	valid-rmse:0.383791
[39]	train-rmse:0.331027	valid-rmse:0.381855
Iteration No: 608 ended. Search finished for the next optimal point.
Time taken: 43.3336
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 609 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 174, 'eta': 0.1886820917520734, 'colsample_bytree': 0.72272679042692312, 'max_depth': 62, 'subsample': 1.0, 'lambda': 17.085374649246887, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87687	valid-rmse:4.8948
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.718413	valid-rmse:0.750238
[20]	train-rmse:0.357531	valid-rmse:0.404296
[30]	train-rmse:0.336008	valid-rmse:0.384835
[39]	train-rmse:0.330932	valid-rmse:0.381402
Iteration No: 609 ended. Search finished for the next optimal point.
Time taken: 40.0859
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 610 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 129, 'eta': 0.17293578686928388, 'colsample_bytree': 0.7386489473052601, 'max_depth': 76, 'subsample': 1.0, 'lambda': 23.554430867147016, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97087	valid-rmse:4.98879
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.845256	valid-rmse:0.874615
[20]	train-rmse:0.372565	valid-rmse:0.418697
[30]	train-rmse:0.33732	valid-rmse:0.38633
[39]	train-rmse:0.330411	valid-rmse:0.38124
Iteration No: 610 ended. Search finished for the next optimal point.
Time taken: 39.1448
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 611 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 125, 'eta': 0.23673128155690082, 'colsample_bytree': 1.0, 'max_depth': 85, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.59398	valid-rmse:4.61219
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.499697	valid-rmse:0.539377
[20]	train-rmse:0.348553	valid-rmse:0.395722
[30]	train-rmse:0.335976	valid-rmse:0.385311
[39]	train-rmse:0.330603	valid-rmse:0.381667
Iteration No: 611 ended. Search finished for the next optimal point.
Time taken: 42.2975
Function value obtained: 0.3817
Current minimum: 0.3798
Iteration No: 612 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.16416278515033186, 'colsample_bytree': 1.0, 'max_depth': 131, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02025	valid-rmse:5.0378
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.907389	valid-rmse:0.93505
[20]	train-rmse:0.368844	valid-rmse:0.41688
[30]	train-rmse:0.33492	valid-rmse:0.38548
[39]	train-rmse:0.33078	valid-rmse:0.382366
Iteration No: 612 ended. Search finished for the next optimal point.
Time taken: 47.1311
Function value obtained: 0.3824
Current minimum: 0.3798
Iteration No: 613 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 72, 'eta': 0.21598084972339532, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.71711	valid-rmse:4.73529
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.577004	valid-rmse:0.614094
[20]	train-rmse:0.351299	valid-rmse:0.399607
[30]	train-rmse:0.334696	valid-rmse:0.385466
[39]	train-rmse:0.328844	valid-rmse:0.381891
Iteration No: 613 ended. Search finished for the next optimal point.
Time taken: 44.1146
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 614 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 169, 'eta': 0.1798624313563654, 'colsample_bytree': 0.63412620117277285, 'max_depth': 68, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92659	valid-rmse:4.94413
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.764986	valid-rmse:0.795409
[20]	train-rmse:0.35205	valid-rmse:0.400845
[30]	train-rmse:0.332324	valid-rmse:0.382802
[39]	train-rmse:0.328775	valid-rmse:0.380772
Iteration No: 614 ended. Search finished for the next optimal point.
Time taken: 41.5332
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 615 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 170, 'eta': 0.1799431403567045, 'colsample_bytree': 0.63531497778592061, 'max_depth': 68, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92612	valid-rmse:4.94365
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.76489	valid-rmse:0.795199
[20]	train-rmse:0.352305	valid-rmse:0.400869
[30]	train-rmse:0.33291	valid-rmse:0.383221
[39]	train-rmse:0.329094	valid-rmse:0.38058
Iteration No: 615 ended. Search finished for the next optimal point.
Time taken: 42.0107
Function value obtained: 0.3806
Current minimum: 0.3798
Iteration No: 616 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 75, 'eta': 0.26508982316864149, 'colsample_bytree': 0.68055160863448749, 'max_depth': 93, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.42612	valid-rmse:4.4444
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.436119	valid-rmse:0.478987
[20]	train-rmse:0.343277	valid-rmse:0.39183
[30]	train-rmse:0.331989	valid-rmse:0.383335
[39]	train-rmse:0.327458	valid-rmse:0.381116
Iteration No: 616 ended. Search finished for the next optimal point.
Time taken: 39.9828
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 617 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 70, 'eta': 0.25373864796616508, 'colsample_bytree': 1.0, 'max_depth': 79, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.49308	valid-rmse:4.51133
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.455347	valid-rmse:0.497848
[20]	train-rmse:0.343744	valid-rmse:0.393139
[30]	train-rmse:0.332635	valid-rmse:0.384785
[39]	train-rmse:0.328071	valid-rmse:0.382487
Iteration No: 617 ended. Search finished for the next optimal point.
Time taken: 46.8267
Function value obtained: 0.3825
Current minimum: 0.3798
Iteration No: 618 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 290, 'eta': 0.29624995693274281, 'colsample_bytree': 0.99047920459263861, 'max_depth': 117, 'subsample': 0.98986196989567576, 'lambda': 0.29044004466829032, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.23288	valid-rmse:4.25028
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.374813	valid-rmse:0.419622
[20]	train-rmse:0.342827	valid-rmse:0.389243
[30]	train-rmse:0.339693	valid-rmse:0.386699
[39]	train-rmse:0.337951	valid-rmse:0.385407
Iteration No: 618 ended. Search finished for the next optimal point.
Time taken: 46.1282
Function value obtained: 0.3854
Current minimum: 0.3798
Iteration No: 619 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 132, 'eta': 0.17350646843091569, 'colsample_bytree': 0.73180296147650159, 'max_depth': 75, 'subsample': 1.0, 'lambda': 22.69591366176099, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96744	valid-rmse:4.98536
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.839653	valid-rmse:0.869103
[20]	train-rmse:0.371525	valid-rmse:0.417854
[30]	train-rmse:0.336982	valid-rmse:0.386109
[39]	train-rmse:0.330408	valid-rmse:0.381276
Iteration No: 619 ended. Search finished for the next optimal point.
Time taken: 40.0154
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 620 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 173, 'eta': 0.19036346123782827, 'colsample_bytree': 0.73190437829783739, 'max_depth': 61, 'subsample': 1.0, 'lambda': 19.159526647429239, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86703	valid-rmse:4.88496
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.707357	valid-rmse:0.73937
[20]	train-rmse:0.356989	valid-rmse:0.403861
[30]	train-rmse:0.336009	valid-rmse:0.384625
[39]	train-rmse:0.331009	valid-rmse:0.381159
Iteration No: 620 ended. Search finished for the next optimal point.
Time taken: 40.7386
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 621 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 131, 'eta': 0.17351256448201277, 'colsample_bytree': 0.73314058928001502, 'max_depth': 75, 'subsample': 1.0, 'lambda': 22.843509493841044, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96741	valid-rmse:4.98533
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.839757	valid-rmse:0.869217
[20]	train-rmse:0.371469	valid-rmse:0.417773
[30]	train-rmse:0.337042	valid-rmse:0.38601
[39]	train-rmse:0.330692	valid-rmse:0.381441
Iteration No: 621 ended. Search finished for the next optimal point.
Time taken: 42.3158
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 622 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 46.822623530959241, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.2167	valid-rmse:4.23515
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.387089	valid-rmse:0.431648
[20]	train-rmse:0.341902	valid-rmse:0.389004
[30]	train-rmse:0.335342	valid-rmse:0.384197
[39]	train-rmse:0.332319	valid-rmse:0.382472
Iteration No: 622 ended. Search finished for the next optimal point.
Time taken: 45.6855
Function value obtained: 0.3825
Current minimum: 0.3798
Iteration No: 623 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 97, 'eta': 0.17955244781650087, 'colsample_bytree': 1.0, 'max_depth': 58, 'subsample': 1.0, 'lambda': 33.443774429974972, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93173	valid-rmse:4.9499
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.791138	valid-rmse:0.822127
[20]	train-rmse:0.366096	valid-rmse:0.413905
[30]	train-rmse:0.335823	valid-rmse:0.386533
[39]	train-rmse:0.329537	valid-rmse:0.382136
Iteration No: 623 ended. Search finished for the next optimal point.
Time taken: 45.3889
Function value obtained: 0.3821
Current minimum: 0.3798
Iteration No: 624 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 170, 'eta': 0.18027173720186052, 'colsample_bytree': 0.63410387289907899, 'max_depth': 68, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92416	valid-rmse:4.94169
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.762211	valid-rmse:0.792487
[20]	train-rmse:0.352316	valid-rmse:0.40071
[30]	train-rmse:0.332973	valid-rmse:0.383038
[39]	train-rmse:0.329374	valid-rmse:0.380448
Iteration No: 624 ended. Search finished for the next optimal point.
Time taken: 43.9705
Function value obtained: 0.3804
Current minimum: 0.3798
Iteration No: 625 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 176, 'eta': 0.19103878422867315, 'colsample_bytree': 0.733224824125839, 'max_depth': 61, 'subsample': 1.0, 'lambda': 18.58988022151253, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86299	valid-rmse:4.88091
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.702734	valid-rmse:0.735002
[20]	train-rmse:0.356791	valid-rmse:0.403699
[30]	train-rmse:0.335882	valid-rmse:0.38481
[39]	train-rmse:0.330449	valid-rmse:0.380883
Iteration No: 625 ended. Search finished for the next optimal point.
Time taken: 39.1457
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 626 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26685201796657043, 'colsample_bytree': 1.0, 'max_depth': 82, 'subsample': 1.0, 'lambda': 54.609800563652762, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4138	valid-rmse:4.43215
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.427463	valid-rmse:0.470436
[20]	train-rmse:0.345033	valid-rmse:0.391186
[30]	train-rmse:0.336485	valid-rmse:0.383974
[39]	train-rmse:0.333203	valid-rmse:0.38193
Iteration No: 626 ended. Search finished for the next optimal point.
Time taken: 45.2217
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 627 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 170, 'eta': 0.18015672579189046, 'colsample_bytree': 0.63468016983338127, 'max_depth': 68, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92484	valid-rmse:4.94238
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.762892	valid-rmse:0.793148
[20]	train-rmse:0.352372	valid-rmse:0.400784
[30]	train-rmse:0.333044	valid-rmse:0.383169
[39]	train-rmse:0.329472	valid-rmse:0.380862
Iteration No: 627 ended. Search finished for the next optimal point.
Time taken: 43.8845
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 628 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 176, 'eta': 0.19133038611065051, 'colsample_bytree': 0.7367945634694284, 'max_depth': 61, 'subsample': 1.0, 'lambda': 19.469488486856555, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8613	valid-rmse:4.87922
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.701039	valid-rmse:0.733508
[20]	train-rmse:0.357135	valid-rmse:0.404079
[30]	train-rmse:0.336347	valid-rmse:0.385102
[39]	train-rmse:0.330882	valid-rmse:0.38126
Iteration No: 628 ended. Search finished for the next optimal point.
Time taken: 39.7243
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 629 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 228, 'eta': 0.19880611812835769, 'colsample_bytree': 1.0, 'max_depth': 64, 'subsample': 1.0, 'lambda': 36.626600702925586, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8174	valid-rmse:4.83561
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.657908	valid-rmse:0.691907
[20]	train-rmse:0.356926	valid-rmse:0.403481
[30]	train-rmse:0.338177	valid-rmse:0.386193
[39]	train-rmse:0.33293	valid-rmse:0.382192
Iteration No: 629 ended. Search finished for the next optimal point.
Time taken: 42.9105
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 630 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 151, 'eta': 0.16547387106059855, 'colsample_bytree': 1.0, 'max_depth': 87, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.0124	valid-rmse:5.03003
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.89371	valid-rmse:0.921599
[20]	train-rmse:0.365779	valid-rmse:0.414042
[30]	train-rmse:0.333919	valid-rmse:0.384707
[39]	train-rmse:0.329508	valid-rmse:0.381579
Iteration No: 630 ended. Search finished for the next optimal point.
Time taken: 50.8500
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 631 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 166, 'eta': 0.16737685124075966, 'colsample_bytree': 1.0, 'max_depth': 169, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00106	valid-rmse:5.01864
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.876167	valid-rmse:0.9044
[20]	train-rmse:0.364709	valid-rmse:0.413146
[30]	train-rmse:0.334982	valid-rmse:0.385734
[39]	train-rmse:0.330636	valid-rmse:0.382542
Iteration No: 631 ended. Search finished for the next optimal point.
Time taken: 48.3013
Function value obtained: 0.3825
Current minimum: 0.3798
Iteration No: 632 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.18626423230025035, 'colsample_bytree': 1.0, 'max_depth': 173, 'subsample': 1.0, 'lambda': 39.358584649598356, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89205	valid-rmse:4.91024
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.740615	valid-rmse:0.772608
[20]	train-rmse:0.362923	valid-rmse:0.409756
[30]	train-rmse:0.337522	valid-rmse:0.386366
[39]	train-rmse:0.33125	valid-rmse:0.381804
Iteration No: 632 ended. Search finished for the next optimal point.
Time taken: 42.6779
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 633 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 119, 'eta': 0.24992617788763849, 'colsample_bytree': 1.0, 'max_depth': 138, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.5157	valid-rmse:4.53394
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.463684	valid-rmse:0.505146
[20]	train-rmse:0.345898	valid-rmse:0.393521
[30]	train-rmse:0.333995	valid-rmse:0.383854
[39]	train-rmse:0.329398	valid-rmse:0.381167
Iteration No: 633 ended. Search finished for the next optimal point.
Time taken: 46.7759
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 634 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.17220300662034282, 'colsample_bytree': 0.71760645977155613, 'max_depth': 78, 'subsample': 1.0, 'lambda': 19.765346547991893, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97509	valid-rmse:4.99301
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.850481	valid-rmse:0.879677
[20]	train-rmse:0.371993	valid-rmse:0.418318
[30]	train-rmse:0.336784	valid-rmse:0.385933
[39]	train-rmse:0.330094	valid-rmse:0.380909
Iteration No: 634 ended. Search finished for the next optimal point.
Time taken: 40.5310
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 635 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 147, 'eta': 0.24749936824021515, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.5301	valid-rmse:4.54835
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.471295	valid-rmse:0.51244
[20]	train-rmse:0.347283	valid-rmse:0.395149
[30]	train-rmse:0.33539	valid-rmse:0.385205
[39]	train-rmse:0.33118	valid-rmse:0.382763
Iteration No: 635 ended. Search finished for the next optimal point.
Time taken: 48.7384
Function value obtained: 0.3828
Current minimum: 0.3798
Iteration No: 636 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 152, 'eta': 0.17236135952280054, 'colsample_bytree': 0.61449674389484965, 'max_depth': 77, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97137	valid-rmse:4.98897
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.829512	valid-rmse:0.858577
[20]	train-rmse:0.358025	valid-rmse:0.406382
[30]	train-rmse:0.332754	valid-rmse:0.383402
[39]	train-rmse:0.328734	valid-rmse:0.380602
Iteration No: 636 ended. Search finished for the next optimal point.
Time taken: 43.5597
Function value obtained: 0.3806
Current minimum: 0.3798
Iteration No: 637 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.17272020963671422, 'colsample_bytree': 0.62378065018412743, 'max_depth': 77, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96923	valid-rmse:4.98681
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.826024	valid-rmse:0.855293
[20]	train-rmse:0.357789	valid-rmse:0.406423
[30]	train-rmse:0.332595	valid-rmse:0.383561
[39]	train-rmse:0.328878	valid-rmse:0.381063
Iteration No: 637 ended. Search finished for the next optimal point.
Time taken: 42.5342
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 638 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 47.324639030960959, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21673	valid-rmse:4.23517
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.387803	valid-rmse:0.432236
[20]	train-rmse:0.341802	valid-rmse:0.388607
[30]	train-rmse:0.33521	valid-rmse:0.383879
[39]	train-rmse:0.332342	valid-rmse:0.382493
Iteration No: 638 ended. Search finished for the next optimal point.
Time taken: 47.2507
Function value obtained: 0.3825
Current minimum: 0.3798
Iteration No: 639 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.17162702284554585, 'colsample_bytree': 0.61215280342802247, 'max_depth': 79, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97641	valid-rmse:4.99404
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.836029	valid-rmse:0.865204
[20]	train-rmse:0.358974	valid-rmse:0.407477
[30]	train-rmse:0.332736	valid-rmse:0.383408
[39]	train-rmse:0.328992	valid-rmse:0.380774
Iteration No: 639 ended. Search finished for the next optimal point.
Time taken: 45.1951
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 640 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26767635734243789, 'colsample_bytree': 1.0, 'max_depth': 170, 'subsample': 1.0, 'lambda': 38.305650143458251, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.40822	valid-rmse:4.42657
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.422425	valid-rmse:0.465245
[20]	train-rmse:0.343592	valid-rmse:0.389629
[30]	train-rmse:0.335453	valid-rmse:0.383161
[39]	train-rmse:0.332191	valid-rmse:0.381152
Iteration No: 640 ended. Search finished for the next optimal point.
Time taken: 48.7535
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 641 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.18984512773617163, 'colsample_bytree': 1.0, 'max_depth': 69, 'subsample': 1.0, 'lambda': 54.441665972775127, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87121	valid-rmse:4.88941
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.717916	valid-rmse:0.750146
[20]	train-rmse:0.361631	valid-rmse:0.408418
[30]	train-rmse:0.338055	valid-rmse:0.386663
[39]	train-rmse:0.331525	valid-rmse:0.381745
Iteration No: 641 ended. Search finished for the next optimal point.
Time taken: 46.5627
Function value obtained: 0.3817
Current minimum: 0.3798
Iteration No: 642 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 111, 'eta': 0.17179652301975112, 'colsample_bytree': 0.40000000000000002, 'max_depth': 76, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97506	valid-rmse:4.99261
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.83788	valid-rmse:0.867101
[20]	train-rmse:0.362316	valid-rmse:0.411683
[30]	train-rmse:0.334291	valid-rmse:0.386368
[39]	train-rmse:0.329217	valid-rmse:0.382817
Iteration No: 642 ended. Search finished for the next optimal point.
Time taken: 39.4841
Function value obtained: 0.3828
Current minimum: 0.3798
Iteration No: 643 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.17329642143710211, 'colsample_bytree': 1.0, 'max_depth': 65, 'subsample': 1.0, 'lambda': 22.162182889142439, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96845	valid-rmse:4.98643
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.840499	valid-rmse:0.869855
[20]	train-rmse:0.370922	valid-rmse:0.417231
[30]	train-rmse:0.337371	valid-rmse:0.386289
[39]	train-rmse:0.330876	valid-rmse:0.381348
Iteration No: 643 ended. Search finished for the next optimal point.
Time taken: 45.3108
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 644 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 143, 'eta': 0.27633328510084076, 'colsample_bytree': 1.0, 'max_depth': 78, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.35908	valid-rmse:4.37738
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.417649	valid-rmse:0.461009
[20]	train-rmse:0.342846	valid-rmse:0.390764
[30]	train-rmse:0.333356	valid-rmse:0.383709
[39]	train-rmse:0.3296	valid-rmse:0.38191
Iteration No: 644 ended. Search finished for the next optimal point.
Time taken: 47.2177
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 645 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 172, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21879	valid-rmse:4.23714
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391817	valid-rmse:0.436696
[20]	train-rmse:0.340491	valid-rmse:0.388882
[30]	train-rmse:0.332678	valid-rmse:0.383832
[39]	train-rmse:0.329126	valid-rmse:0.38221
Iteration No: 645 ended. Search finished for the next optimal point.
Time taken: 50.3015
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 646 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 199, 'eta': 0.18617316092838609, 'colsample_bytree': 1.0, 'max_depth': 57, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8889	valid-rmse:4.90641
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.716903	valid-rmse:0.748376
[20]	train-rmse:0.3497	valid-rmse:0.398547
[30]	train-rmse:0.333878	valid-rmse:0.384114
[39]	train-rmse:0.330528	valid-rmse:0.382182
Iteration No: 646 ended. Search finished for the next optimal point.
Time taken: 49.7137
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 647 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 86, 'eta': 0.26612105743836345, 'colsample_bytree': 0.68301607464337244, 'max_depth': 95, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.42	valid-rmse:4.43829
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.434463	valid-rmse:0.477534
[20]	train-rmse:0.343292	valid-rmse:0.391942
[30]	train-rmse:0.332447	valid-rmse:0.384007
[39]	train-rmse:0.328324	valid-rmse:0.382296
Iteration No: 647 ended. Search finished for the next optimal point.
Time taken: 42.6373
Function value obtained: 0.3823
Current minimum: 0.3798
Iteration No: 648 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.17284648886752321, 'colsample_bytree': 0.74573090596610525, 'max_depth': 79, 'subsample': 1.0, 'lambda': 22.000793550032746, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97133	valid-rmse:4.98925
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.844933	valid-rmse:0.874253
[20]	train-rmse:0.371945	valid-rmse:0.418173
[30]	train-rmse:0.337382	valid-rmse:0.386567
[39]	train-rmse:0.330904	valid-rmse:0.381567
Iteration No: 648 ended. Search finished for the next optimal point.
Time taken: 43.5487
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 649 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.23241005522488731, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 35.481197886361976, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.6176	valid-rmse:4.63588
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.505614	valid-rmse:0.544931
[20]	train-rmse:0.347187	valid-rmse:0.393425
[30]	train-rmse:0.33681	valid-rmse:0.384486
[39]	train-rmse:0.332985	valid-rmse:0.381677
Iteration No: 649 ended. Search finished for the next optimal point.
Time taken: 45.1577
Function value obtained: 0.3817
Current minimum: 0.3798
Iteration No: 650 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 92, 'eta': 0.21627208743496801, 'colsample_bytree': 1.0, 'max_depth': 165, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.71539	valid-rmse:4.73357
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.575895	valid-rmse:0.6129
[20]	train-rmse:0.352231	valid-rmse:0.400321
[30]	train-rmse:0.335718	valid-rmse:0.385941
[39]	train-rmse:0.3302	valid-rmse:0.382156
Iteration No: 650 ended. Search finished for the next optimal point.
Time taken: 49.0859
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 651 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 177, 'eta': 0.17647156681752374, 'colsample_bytree': 0.67333987336027556, 'max_depth': 72, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.94683	valid-rmse:4.96437
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.793237	valid-rmse:0.82282
[20]	train-rmse:0.355507	valid-rmse:0.403645
[30]	train-rmse:0.333377	valid-rmse:0.383518
[39]	train-rmse:0.329401	valid-rmse:0.380722
Iteration No: 651 ended. Search finished for the next optimal point.
Time taken: 45.6774
Function value obtained: 0.3807
Current minimum: 0.3798
Iteration No: 652 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.18995032457486394, 'colsample_bytree': 0.72720137200129753, 'max_depth': 61, 'subsample': 1.0, 'lambda': 18.653077219140016, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86947	valid-rmse:4.88739
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.710053	valid-rmse:0.742146
[20]	train-rmse:0.35735	valid-rmse:0.404031
[30]	train-rmse:0.335888	valid-rmse:0.384495
[39]	train-rmse:0.330578	valid-rmse:0.380591
Iteration No: 652 ended. Search finished for the next optimal point.
Time taken: 42.5068
Function value obtained: 0.3806
Current minimum: 0.3798
Iteration No: 653 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 182, 'eta': 0.18376365058519248, 'colsample_bytree': 0.65781389574167792, 'max_depth': 66, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90331	valid-rmse:4.92083
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.734768	valid-rmse:0.76578
[20]	train-rmse:0.350488	valid-rmse:0.39911
[30]	train-rmse:0.332943	valid-rmse:0.383029
[39]	train-rmse:0.32972	valid-rmse:0.380952
Iteration No: 653 ended. Search finished for the next optimal point.
Time taken: 46.4191
Function value obtained: 0.3810
Current minimum: 0.3798
Iteration No: 654 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26690421666142561, 'colsample_bytree': 1.0, 'max_depth': 170, 'subsample': 1.0, 'lambda': 38.577366315291705, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41282	valid-rmse:4.43117
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.425015	valid-rmse:0.467917
[20]	train-rmse:0.34447	valid-rmse:0.390799
[30]	train-rmse:0.336306	valid-rmse:0.384267
[39]	train-rmse:0.33307	valid-rmse:0.382212
Iteration No: 654 ended. Search finished for the next optimal point.
Time taken: 48.0868
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 655 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 182, 'eta': 0.18355654223866821, 'colsample_bytree': 0.65857483183727172, 'max_depth': 66, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90454	valid-rmse:4.92206
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.736322	valid-rmse:0.767316
[20]	train-rmse:0.350547	valid-rmse:0.399022
[30]	train-rmse:0.332968	valid-rmse:0.383016
[39]	train-rmse:0.329741	valid-rmse:0.380978
Iteration No: 655 ended. Search finished for the next optimal point.
Time taken: 46.6554
Function value obtained: 0.3810
Current minimum: 0.3798
Iteration No: 656 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 136, 'eta': 0.23658607895266542, 'colsample_bytree': 1.0, 'max_depth': 87, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.59484	valid-rmse:4.61305
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.500488	valid-rmse:0.540124
[20]	train-rmse:0.348824	valid-rmse:0.396247
[30]	train-rmse:0.335242	valid-rmse:0.384713
[39]	train-rmse:0.330672	valid-rmse:0.381932
Iteration No: 656 ended. Search finished for the next optimal point.
Time taken: 46.8859
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 657 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 168, 'eta': 0.19081849443722795, 'colsample_bytree': 0.73478517853629943, 'max_depth': 61, 'subsample': 1.0, 'lambda': 21.100620530873584, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86439	valid-rmse:4.88232
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.704683	valid-rmse:0.7369
[20]	train-rmse:0.357125	valid-rmse:0.404047
[30]	train-rmse:0.336153	valid-rmse:0.384929
[39]	train-rmse:0.33075	valid-rmse:0.381162
Iteration No: 657 ended. Search finished for the next optimal point.
Time taken: 44.0286
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 658 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 167, 'eta': 0.19016762872346302, 'colsample_bytree': 0.73434679909838441, 'max_depth': 61, 'subsample': 1.0, 'lambda': 21.135895442578875, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86826	valid-rmse:4.8862
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.709286	valid-rmse:0.741481
[20]	train-rmse:0.357346	valid-rmse:0.404323
[30]	train-rmse:0.335891	valid-rmse:0.38497
[39]	train-rmse:0.330875	valid-rmse:0.381515
Iteration No: 658 ended. Search finished for the next optimal point.
Time taken: 43.9945
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 659 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 137, 'eta': 0.17268663447839144, 'colsample_bytree': 0.74440759749769048, 'max_depth': 79, 'subsample': 1.0, 'lambda': 21.540167897928271, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97227	valid-rmse:4.99019
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.846376	valid-rmse:0.87561
[20]	train-rmse:0.37207	valid-rmse:0.4181
[30]	train-rmse:0.337539	valid-rmse:0.386415
[39]	train-rmse:0.331195	valid-rmse:0.381842
Iteration No: 659 ended. Search finished for the next optimal point.
Time taken: 42.3748
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 660 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 166, 'eta': 0.19074571699749626, 'colsample_bytree': 0.73280468204888027, 'max_depth': 61, 'subsample': 1.0, 'lambda': 21.409811350959092, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86484	valid-rmse:4.88277
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.705074	valid-rmse:0.737319
[20]	train-rmse:0.356818	valid-rmse:0.403637
[30]	train-rmse:0.335642	valid-rmse:0.384363
[39]	train-rmse:0.330157	valid-rmse:0.380464
Iteration No: 660 ended. Search finished for the next optimal point.
Time taken: 43.4257
Function value obtained: 0.3805
Current minimum: 0.3798
Iteration No: 661 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 168, 'eta': 0.19092301417346119, 'colsample_bytree': 0.73505850829336028, 'max_depth': 61, 'subsample': 1.0, 'lambda': 21.165322908425086, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86377	valid-rmse:4.8817
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.703993	valid-rmse:0.736227
[20]	train-rmse:0.357048	valid-rmse:0.403918
[30]	train-rmse:0.336267	valid-rmse:0.385249
[39]	train-rmse:0.330749	valid-rmse:0.38128
Iteration No: 661 ended. Search finished for the next optimal point.
Time taken: 43.7405
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 662 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 129, 'eta': 0.26571238369675199, 'colsample_bytree': 1.0, 'max_depth': 164, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.42206	valid-rmse:4.44034
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.432812	valid-rmse:0.475528
[20]	train-rmse:0.342958	valid-rmse:0.390621
[30]	train-rmse:0.333362	valid-rmse:0.383285
[39]	train-rmse:0.329158	valid-rmse:0.38113
Iteration No: 662 ended. Search finished for the next optimal point.
Time taken: 50.9955
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 663 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.2276775959869595, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 34.660814992192371, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.64569	valid-rmse:4.66396
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.522078	valid-rmse:0.560514
[20]	train-rmse:0.348394	valid-rmse:0.394655
[30]	train-rmse:0.337525	valid-rmse:0.385039
[39]	train-rmse:0.333392	valid-rmse:0.382008
Iteration No: 663 ended. Search finished for the next optimal point.
Time taken: 48.3350
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 664 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 148, 'eta': 0.18889889234263971, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 43.627182393480147, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87651	valid-rmse:4.89471
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.72278	valid-rmse:0.755063
[20]	train-rmse:0.361599	valid-rmse:0.408003
[30]	train-rmse:0.337487	valid-rmse:0.385923
[39]	train-rmse:0.331154	valid-rmse:0.381352
Iteration No: 664 ended. Search finished for the next optimal point.
Time taken: 47.6211
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 665 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 141, 'eta': 0.17364026325560877, 'colsample_bytree': 0.74285469688643713, 'max_depth': 77, 'subsample': 1.0, 'lambda': 21.529073448215446, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96659	valid-rmse:4.98451
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.837943	valid-rmse:0.867334
[20]	train-rmse:0.371018	valid-rmse:0.417189
[30]	train-rmse:0.337458	valid-rmse:0.386374
[39]	train-rmse:0.330911	valid-rmse:0.381244
Iteration No: 665 ended. Search finished for the next optimal point.
Time taken: 43.8285
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 666 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 167, 'eta': 0.19109384623082759, 'colsample_bytree': 0.73633612309780938, 'max_depth': 61, 'subsample': 1.0, 'lambda': 21.561427881763649, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.86277	valid-rmse:4.88071
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.702782	valid-rmse:0.735089
[20]	train-rmse:0.356871	valid-rmse:0.403794
[30]	train-rmse:0.335746	valid-rmse:0.384738
[39]	train-rmse:0.330592	valid-rmse:0.381172
Iteration No: 666 ended. Search finished for the next optimal point.
Time taken: 45.3058
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 667 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 150, 'eta': 0.1896636755436043, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 44.154396756323521, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.87198	valid-rmse:4.89018
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.717971	valid-rmse:0.750201
[20]	train-rmse:0.361374	valid-rmse:0.407726
[30]	train-rmse:0.337813	valid-rmse:0.386164
[39]	train-rmse:0.331684	valid-rmse:0.381729
Iteration No: 667 ended. Search finished for the next optimal point.
Time taken: 45.9777
Function value obtained: 0.3817
Current minimum: 0.3798
Iteration No: 668 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 287, 'eta': 0.21940558540692756, 'colsample_bytree': 0.8848248376320248, 'max_depth': 43, 'subsample': 0.97919158161137254, 'lambda': 0.77563960172220914, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.69176	valid-rmse:4.70949
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.534252	valid-rmse:0.571724
[20]	train-rmse:0.347335	valid-rmse:0.393879
[30]	train-rmse:0.339695	valid-rmse:0.386747
[39]	train-rmse:0.337597	valid-rmse:0.385101
Iteration No: 668 ended. Search finished for the next optimal point.
Time taken: 46.7432
Function value obtained: 0.3851
Current minimum: 0.3798
Iteration No: 669 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 155, 'eta': 0.16370931429962449, 'colsample_bytree': 1.0, 'max_depth': 102, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.02295	valid-rmse:5.04057
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.911281	valid-rmse:0.938772
[20]	train-rmse:0.368336	valid-rmse:0.416455
[30]	train-rmse:0.334192	valid-rmse:0.384988
[39]	train-rmse:0.329685	valid-rmse:0.381704
Iteration No: 669 ended. Search finished for the next optimal point.
Time taken: 50.7308
Function value obtained: 0.3817
Current minimum: 0.3798
Iteration No: 670 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 114, 'eta': 0.18010787179179794, 'colsample_bytree': 1.0, 'max_depth': 57, 'subsample': 1.0, 'lambda': 29.299118067042354, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92821	valid-rmse:4.9462
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.785414	valid-rmse:0.816157
[20]	train-rmse:0.364834	valid-rmse:0.412012
[30]	train-rmse:0.336129	valid-rmse:0.386015
[39]	train-rmse:0.329545	valid-rmse:0.381469
Iteration No: 670 ended. Search finished for the next optimal point.
Time taken: 47.9895
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 671 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26324120340165125, 'colsample_bytree': 1.0, 'max_depth': 67, 'subsample': 1.0, 'lambda': 33.984709475760106, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.43434	valid-rmse:4.45269
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.429245	valid-rmse:0.471991
[20]	train-rmse:0.344083	valid-rmse:0.390972
[30]	train-rmse:0.335783	valid-rmse:0.384328
[39]	train-rmse:0.332372	valid-rmse:0.381963
Iteration No: 671 ended. Search finished for the next optimal point.
Time taken: 48.4719
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 672 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 162, 'eta': 0.18818889964761121, 'colsample_bytree': 0.40000000000000002, 'max_depth': 53, 'subsample': 1.0, 'lambda': 28.283767133223211, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88042	valid-rmse:4.89831
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.731296	valid-rmse:0.763152
[20]	train-rmse:0.367137	valid-rmse:0.412957
[30]	train-rmse:0.340282	valid-rmse:0.388308
[39]	train-rmse:0.333315	valid-rmse:0.382975
Iteration No: 672 ended. Search finished for the next optimal point.
Time taken: 39.5403
Function value obtained: 0.3830
Current minimum: 0.3798
Iteration No: 673 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 160, 'eta': 0.17023563322176688, 'colsample_bytree': 0.65539282616933114, 'max_depth': 84, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98402	valid-rmse:5.00156
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.848236	valid-rmse:0.876767
[20]	train-rmse:0.360339	valid-rmse:0.408445
[30]	train-rmse:0.332818	valid-rmse:0.383186
[39]	train-rmse:0.328661	valid-rmse:0.380146
Iteration No: 673 ended. Search finished for the next optimal point.
Time taken: 48.7143
Function value obtained: 0.3801
Current minimum: 0.3798
Iteration No: 674 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 112, 'eta': 0.25160778975615772, 'colsample_bytree': 0.78946638757656729, 'max_depth': 163, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.50606	valid-rmse:4.52431
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.461527	valid-rmse:0.50299
[20]	train-rmse:0.34585	valid-rmse:0.393343
[30]	train-rmse:0.33372	valid-rmse:0.383668
[39]	train-rmse:0.329196	valid-rmse:0.381059
Iteration No: 674 ended. Search finished for the next optimal point.
Time taken: 49.6546
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 675 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 185, 'eta': 0.23895609865871412, 'colsample_bytree': 1.0, 'max_depth': 137, 'subsample': 1.0, 'lambda': 66.650979483407369, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.58002	valid-rmse:4.59826
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.490726	valid-rmse:0.530534
[20]	train-rmse:0.347647	valid-rmse:0.39433
[30]	train-rmse:0.335734	valid-rmse:0.38431
[39]	train-rmse:0.331521	valid-rmse:0.38195
Iteration No: 675 ended. Search finished for the next optimal point.
Time taken: 49.8658
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 676 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 154, 'eta': 0.16493988562350681, 'colsample_bytree': 1.0, 'max_depth': 93, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.0156	valid-rmse:5.03323
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.899065	valid-rmse:0.926841
[20]	train-rmse:0.366586	valid-rmse:0.415026
[30]	train-rmse:0.33399	valid-rmse:0.385007
[39]	train-rmse:0.329595	valid-rmse:0.381757
Iteration No: 676 ended. Search finished for the next optimal point.
Time taken: 52.8612
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 677 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 135, 'eta': 0.27367008411700661, 'colsample_bytree': 1.0, 'max_depth': 170, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.37488	valid-rmse:4.39316
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.419765	valid-rmse:0.463317
[20]	train-rmse:0.342975	valid-rmse:0.390889
[30]	train-rmse:0.333119	valid-rmse:0.383243
[39]	train-rmse:0.329422	valid-rmse:0.381728
Iteration No: 677 ended. Search finished for the next optimal point.
Time taken: 51.4376
Function value obtained: 0.3817
Current minimum: 0.3798
Iteration No: 678 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.17246608352977966, 'colsample_bytree': 1.0, 'max_depth': 131, 'subsample': 1.0, 'lambda': 25.833992608163427, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97354	valid-rmse:4.99152
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.84889	valid-rmse:0.878132
[20]	train-rmse:0.372869	valid-rmse:0.419147
[30]	train-rmse:0.337824	valid-rmse:0.386847
[39]	train-rmse:0.331053	valid-rmse:0.381769
Iteration No: 678 ended. Search finished for the next optimal point.
Time taken: 50.5692
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 679 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 130, 'eta': 0.27706727053962815, 'colsample_bytree': 0.73656387262578105, 'max_depth': 92, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.355	valid-rmse:4.37334
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.416778	valid-rmse:0.460507
[20]	train-rmse:0.343307	valid-rmse:0.391314
[30]	train-rmse:0.33329	valid-rmse:0.383749
[39]	train-rmse:0.329158	valid-rmse:0.38175
Iteration No: 679 ended. Search finished for the next optimal point.
Time taken: 48.6995
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 680 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 179, 'eta': 0.1800064526581367, 'colsample_bytree': 0.67071116911491635, 'max_depth': 69, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92572	valid-rmse:4.94326
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.764327	valid-rmse:0.794648
[20]	train-rmse:0.352961	valid-rmse:0.401499
[30]	train-rmse:0.333037	valid-rmse:0.383239
[39]	train-rmse:0.329568	valid-rmse:0.380782
Iteration No: 680 ended. Search finished for the next optimal point.
Time taken: 49.6160
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 681 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 178, 'eta': 0.17983748860162513, 'colsample_bytree': 0.67126446190478939, 'max_depth': 70, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92674	valid-rmse:4.94428
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.765629	valid-rmse:0.795875
[20]	train-rmse:0.353128	valid-rmse:0.401543
[30]	train-rmse:0.333312	valid-rmse:0.383394
[39]	train-rmse:0.329702	valid-rmse:0.38098
Iteration No: 681 ended. Search finished for the next optimal point.
Time taken: 48.7254
Function value obtained: 0.3810
Current minimum: 0.3798
Iteration No: 682 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 180, 'eta': 0.18050110270676298, 'colsample_bytree': 0.67071874615984162, 'max_depth': 69, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92277	valid-rmse:4.9403
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.760531	valid-rmse:0.790773
[20]	train-rmse:0.352611	valid-rmse:0.401339
[30]	train-rmse:0.333048	valid-rmse:0.383599
[39]	train-rmse:0.329521	valid-rmse:0.381296
Iteration No: 682 ended. Search finished for the next optimal point.
Time taken: 48.8699
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 683 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.17255960656352035, 'colsample_bytree': 0.74496068257091808, 'max_depth': 81, 'subsample': 1.0, 'lambda': 20.443023381642796, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97297	valid-rmse:4.99089
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.847197	valid-rmse:0.876433
[20]	train-rmse:0.372064	valid-rmse:0.418275
[30]	train-rmse:0.337178	valid-rmse:0.386123
[39]	train-rmse:0.330642	valid-rmse:0.381135
Iteration No: 683 ended. Search finished for the next optimal point.
Time taken: 48.1458
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 684 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.16765214569406131, 'colsample_bytree': 0.64629905329624826, 'max_depth': 92, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99944	valid-rmse:5.01697
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.872717	valid-rmse:0.900877
[20]	train-rmse:0.363248	valid-rmse:0.411196
[30]	train-rmse:0.333293	valid-rmse:0.38386
[39]	train-rmse:0.329129	valid-rmse:0.380969
Iteration No: 684 ended. Search finished for the next optimal point.
Time taken: 49.7538
Function value obtained: 0.3810
Current minimum: 0.3798
Iteration No: 685 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 154, 'eta': 0.2708973878602623, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.3913	valid-rmse:4.40958
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.423219	valid-rmse:0.466123
[20]	train-rmse:0.343721	valid-rmse:0.391012
[30]	train-rmse:0.334254	valid-rmse:0.383896
[39]	train-rmse:0.330114	valid-rmse:0.381429
Iteration No: 685 ended. Search finished for the next optimal point.
Time taken: 51.8295
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 686 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 136, 'eta': 0.17312395279622902, 'colsample_bytree': 0.74625187933223036, 'max_depth': 79, 'subsample': 1.0, 'lambda': 21.125240885448374, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96965	valid-rmse:4.98757
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.842441	valid-rmse:0.871765
[20]	train-rmse:0.371585	valid-rmse:0.417707
[30]	train-rmse:0.337443	valid-rmse:0.386382
[39]	train-rmse:0.330926	valid-rmse:0.381294
Iteration No: 686 ended. Search finished for the next optimal point.
Time taken: 47.0992
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 687 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21879	valid-rmse:4.23714
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391735	valid-rmse:0.43678
[20]	train-rmse:0.340499	valid-rmse:0.388855
[30]	train-rmse:0.332348	valid-rmse:0.38335
[39]	train-rmse:0.328918	valid-rmse:0.382158
Iteration No: 687 ended. Search finished for the next optimal point.
Time taken: 56.2751
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 688 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.24437548298521364, 'colsample_bytree': 1.0, 'max_depth': 75, 'subsample': 1.0, 'lambda': 44.597400015460458, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.54687	valid-rmse:4.56517
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.472952	valid-rmse:0.513484
[20]	train-rmse:0.346997	valid-rmse:0.393248
[30]	train-rmse:0.337328	valid-rmse:0.384775
[39]	train-rmse:0.333383	valid-rmse:0.382144
Iteration No: 688 ended. Search finished for the next optimal point.
Time taken: 50.9486
Function value obtained: 0.3821
Current minimum: 0.3798
Iteration No: 689 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.16784906014822595, 'colsample_bytree': 0.64729360216313658, 'max_depth': 92, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99826	valid-rmse:5.0158
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.87077	valid-rmse:0.898955
[20]	train-rmse:0.362924	valid-rmse:0.410924
[30]	train-rmse:0.33312	valid-rmse:0.383842
[39]	train-rmse:0.328796	valid-rmse:0.380481
Iteration No: 689 ended. Search finished for the next optimal point.
Time taken: 49.0197
Function value obtained: 0.3805
Current minimum: 0.3798
Iteration No: 690 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26400765996157138, 'colsample_bytree': 0.41244827136564838, 'max_depth': 187, 'subsample': 0.87575059650630038, 'lambda': 86.676279147628989, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.43286	valid-rmse:4.45129
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.445994	valid-rmse:0.48788
[20]	train-rmse:0.353419	valid-rmse:0.399077
[30]	train-rmse:0.341001	valid-rmse:0.387981
[39]	train-rmse:0.335884	valid-rmse:0.383884
Iteration No: 690 ended. Search finished for the next optimal point.
Time taken: 41.0441
Function value obtained: 0.3839
Current minimum: 0.3798
Iteration No: 691 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 38, 'eta': 0.29948530418196523, 'colsample_bytree': 0.95395570797496043, 'max_depth': 197, 'subsample': 0.99901727826511055, 'lambda': 89.425621008947687, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.22182	valid-rmse:4.24017
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.391131	valid-rmse:0.436508
[20]	train-rmse:0.345606	valid-rmse:0.392944
[30]	train-rmse:0.338906	valid-rmse:0.387249
[39]	train-rmse:0.336199	valid-rmse:0.385451
Iteration No: 691 ended. Search finished for the next optimal point.
Time taken: 52.7043
Function value obtained: 0.3855
Current minimum: 0.3798
Iteration No: 692 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.16793690438083986, 'colsample_bytree': 0.64638220322509821, 'max_depth': 91, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9984	valid-rmse:5.01597
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.870593	valid-rmse:0.898766
[20]	train-rmse:0.363767	valid-rmse:0.411821
[30]	train-rmse:0.334019	valid-rmse:0.384381
[39]	train-rmse:0.329715	valid-rmse:0.381251
Iteration No: 692 ended. Search finished for the next optimal point.
Time taken: 50.3247
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 693 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 228, 'eta': 0.19364677798338678, 'colsample_bytree': 1.0, 'max_depth': 66, 'subsample': 1.0, 'lambda': 32.504834847590388, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84793	valid-rmse:4.86613
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.689061	valid-rmse:0.722156
[20]	train-rmse:0.358133	valid-rmse:0.404616
[30]	train-rmse:0.338732	valid-rmse:0.386544
[39]	train-rmse:0.333314	valid-rmse:0.382343
Iteration No: 693 ended. Search finished for the next optimal point.
Time taken: 49.6681
Function value obtained: 0.3823
Current minimum: 0.3798
Iteration No: 694 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 146, 'eta': 0.18183453538525413, 'colsample_bytree': 1.0, 'max_depth': 174, 'subsample': 1.0, 'lambda': 34.110603595078778, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91822	valid-rmse:4.93641
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.773838	valid-rmse:0.804909
[20]	train-rmse:0.365516	valid-rmse:0.411819
[30]	train-rmse:0.337214	valid-rmse:0.38581
[39]	train-rmse:0.331278	valid-rmse:0.381525
Iteration No: 694 ended. Search finished for the next optimal point.
Time taken: 48.7772
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 695 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 119, 'eta': 0.25394745666329144, 'colsample_bytree': 1.0, 'max_depth': 135, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.49184	valid-rmse:4.51009
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.454699	valid-rmse:0.4967
[20]	train-rmse:0.345329	valid-rmse:0.393042
[30]	train-rmse:0.33429	valid-rmse:0.384124
[39]	train-rmse:0.329715	valid-rmse:0.381643
Iteration No: 695 ended. Search finished for the next optimal point.
Time taken: 52.4155
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 696 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 155, 'eta': 0.16819965297570197, 'colsample_bytree': 0.64412602913256189, 'max_depth': 90, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99617	valid-rmse:5.0137
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.867898	valid-rmse:0.896132
[20]	train-rmse:0.362622	valid-rmse:0.410812
[30]	train-rmse:0.333399	valid-rmse:0.383855
[39]	train-rmse:0.329139	valid-rmse:0.380806
Iteration No: 696 ended. Search finished for the next optimal point.
Time taken: 48.5657
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 697 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.16694258250629387, 'colsample_bytree': 1.0, 'max_depth': 82, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00365	valid-rmse:5.02127
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.879525	valid-rmse:0.90763
[20]	train-rmse:0.3644	valid-rmse:0.413115
[30]	train-rmse:0.334236	valid-rmse:0.385472
[39]	train-rmse:0.330018	valid-rmse:0.382442
Iteration No: 697 ended. Search finished for the next optimal point.
Time taken: 56.2685
Function value obtained: 0.3824
Current minimum: 0.3798
Iteration No: 698 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 116, 'eta': 0.24859929260483213, 'colsample_bytree': 0.77837153180047114, 'max_depth': 168, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.5239	valid-rmse:4.54215
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.469411	valid-rmse:0.510518
[20]	train-rmse:0.346952	valid-rmse:0.394385
[30]	train-rmse:0.334332	valid-rmse:0.384068
[39]	train-rmse:0.32946	valid-rmse:0.380838
Iteration No: 698 ended. Search finished for the next optimal point.
Time taken: 47.7109
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 699 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 129, 'eta': 0.2689271884238692, 'colsample_bytree': 0.75752008346704236, 'max_depth': 168, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.40326	valid-rmse:4.42158
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.429111	valid-rmse:0.472319
[20]	train-rmse:0.344455	valid-rmse:0.392272
[30]	train-rmse:0.333614	valid-rmse:0.383539
[39]	train-rmse:0.329476	valid-rmse:0.381132
Iteration No: 699 ended. Search finished for the next optimal point.
Time taken: 48.1965
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 700 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 179, 'eta': 0.18377193842401707, 'colsample_bytree': 0.65764166436677152, 'max_depth': 66, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90325	valid-rmse:4.92078
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.734382	valid-rmse:0.765329
[20]	train-rmse:0.350407	valid-rmse:0.398932
[30]	train-rmse:0.332574	valid-rmse:0.382636
[39]	train-rmse:0.329278	valid-rmse:0.380358
Iteration No: 700 ended. Search finished for the next optimal point.
Time taken: 52.1395
Function value obtained: 0.3804
Current minimum: 0.3798
Iteration No: 701 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 124, 'eta': 0.26114527849696745, 'colsample_bytree': 1.0, 'max_depth': 145, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.44915	valid-rmse:4.46741
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.44037	valid-rmse:0.483126
[20]	train-rmse:0.343729	valid-rmse:0.391729
[30]	train-rmse:0.333476	valid-rmse:0.383742
[39]	train-rmse:0.329579	valid-rmse:0.38185
Iteration No: 701 ended. Search finished for the next optimal point.
Time taken: 53.1908
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 702 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 143, 'eta': 0.29999999999999999, 'colsample_bytree': 1.0, 'max_depth': 169, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21879	valid-rmse:4.23714
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.390994	valid-rmse:0.43579
[20]	train-rmse:0.340573	valid-rmse:0.388588
[30]	train-rmse:0.332713	valid-rmse:0.383309
[39]	train-rmse:0.329578	valid-rmse:0.382154
Iteration No: 702 ended. Search finished for the next optimal point.
Time taken: 56.4690
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 703 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.17270883118081884, 'colsample_bytree': 1.0, 'max_depth': 68, 'subsample': 1.0, 'lambda': 14.289380804883612, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97152	valid-rmse:4.9895
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.843287	valid-rmse:0.872436
[20]	train-rmse:0.369615	valid-rmse:0.416003
[30]	train-rmse:0.336992	valid-rmse:0.385874
[39]	train-rmse:0.330751	valid-rmse:0.381254
Iteration No: 703 ended. Search finished for the next optimal point.
Time taken: 53.7935
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 704 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 143, 'eta': 0.23879252082580429, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.58175	valid-rmse:4.59997
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.494002	valid-rmse:0.533824
[20]	train-rmse:0.348508	valid-rmse:0.395576
[30]	train-rmse:0.335881	valid-rmse:0.384782
[39]	train-rmse:0.330942	valid-rmse:0.381628
Iteration No: 704 ended. Search finished for the next optimal point.
Time taken: 54.7886
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 705 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 179, 'eta': 0.18381402314853909, 'colsample_bytree': 0.65969920164890117, 'max_depth': 66, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.903	valid-rmse:4.92053
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.734176	valid-rmse:0.765054
[20]	train-rmse:0.350187	valid-rmse:0.398845
[30]	train-rmse:0.332808	valid-rmse:0.383199
[39]	train-rmse:0.329259	valid-rmse:0.380912
Iteration No: 705 ended. Search finished for the next optimal point.
Time taken: 50.7196
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 706 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 107, 'eta': 0.23794742035665623, 'colsample_bytree': 0.78645681609839868, 'max_depth': 168, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.58708	valid-rmse:4.60531
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.497503	valid-rmse:0.537545
[20]	train-rmse:0.348798	valid-rmse:0.396388
[30]	train-rmse:0.33464	valid-rmse:0.384697
[39]	train-rmse:0.32945	valid-rmse:0.381408
Iteration No: 706 ended. Search finished for the next optimal point.
Time taken: 48.7725
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 707 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 149, 'eta': 0.18141051323294824, 'colsample_bytree': 0.72956649449354583, 'max_depth': 66, 'subsample': 0.80000000000000004, 'lambda': 19.018484602499626, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92044	valid-rmse:4.93844
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.77407	valid-rmse:0.804764
[20]	train-rmse:0.365102	valid-rmse:0.411382
[30]	train-rmse:0.338439	valid-rmse:0.386674
[39]	train-rmse:0.333089	valid-rmse:0.382608
Iteration No: 707 ended. Search finished for the next optimal point.
Time taken: 48.7094
Function value obtained: 0.3826
Current minimum: 0.3798
Iteration No: 708 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 181, 'eta': 0.183717886726672, 'colsample_bytree': 0.66143910021891739, 'max_depth': 66, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90358	valid-rmse:4.92111
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.735157	valid-rmse:0.766205
[20]	train-rmse:0.350192	valid-rmse:0.399048
[30]	train-rmse:0.332841	valid-rmse:0.383098
[39]	train-rmse:0.329388	valid-rmse:0.380776
Iteration No: 708 ended. Search finished for the next optimal point.
Time taken: 50.7880
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 709 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 132, 'eta': 0.2712864954969546, 'colsample_bytree': 0.75263943955995782, 'max_depth': 169, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.38927	valid-rmse:4.40759
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.425336	valid-rmse:0.468582
[20]	train-rmse:0.344531	valid-rmse:0.391973
[30]	train-rmse:0.334125	valid-rmse:0.384022
[39]	train-rmse:0.329796	valid-rmse:0.381533
Iteration No: 709 ended. Search finished for the next optimal point.
Time taken: 50.1468
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 710 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 94, 'eta': 0.17976157578162244, 'colsample_bytree': 0.70545787378894986, 'max_depth': 68, 'subsample': 1.0, 'lambda': 26.229259278841162, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93037	valid-rmse:4.94829
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.788431	valid-rmse:0.818938
[20]	train-rmse:0.365445	valid-rmse:0.412847
[30]	train-rmse:0.335576	valid-rmse:0.385964
[39]	train-rmse:0.328819	valid-rmse:0.381125
Iteration No: 710 ended. Search finished for the next optimal point.
Time taken: 47.8288
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 711 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26727334356550847, 'colsample_bytree': 0.87154769703060464, 'max_depth': 200, 'subsample': 1.0, 'lambda': 40.472268152322215, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41071	valid-rmse:4.42906
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.426546	valid-rmse:0.469171
[20]	train-rmse:0.345069	valid-rmse:0.391202
[30]	train-rmse:0.336222	valid-rmse:0.384047
[39]	train-rmse:0.332724	valid-rmse:0.381618
Iteration No: 711 ended. Search finished for the next optimal point.
Time taken: 51.7439
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 712 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 181, 'eta': 0.18359852129967111, 'colsample_bytree': 0.66111719794613866, 'max_depth': 66, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90429	valid-rmse:4.92182
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.736254	valid-rmse:0.76732
[20]	train-rmse:0.350597	valid-rmse:0.399226
[30]	train-rmse:0.333086	valid-rmse:0.383327
[39]	train-rmse:0.329575	valid-rmse:0.380866
Iteration No: 712 ended. Search finished for the next optimal point.
Time taken: 52.1812
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 713 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 155, 'eta': 0.16743079303638081, 'colsample_bytree': 0.64019440393659932, 'max_depth': 94, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00076	valid-rmse:5.01829
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.87494	valid-rmse:0.903015
[20]	train-rmse:0.363575	valid-rmse:0.411607
[30]	train-rmse:0.333119	valid-rmse:0.383739
[39]	train-rmse:0.328974	valid-rmse:0.380759
Iteration No: 713 ended. Search finished for the next optimal point.
Time taken: 52.1575
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 714 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 88, 'eta': 0.21507721455272671, 'colsample_bytree': 1.0, 'max_depth': 168, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.72248	valid-rmse:4.74066
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.58162	valid-rmse:0.618474
[20]	train-rmse:0.352693	valid-rmse:0.400781
[30]	train-rmse:0.335453	valid-rmse:0.385586
[39]	train-rmse:0.32989	valid-rmse:0.381999
Iteration No: 714 ended. Search finished for the next optimal point.
Time taken: 53.9426
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 715 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 154, 'eta': 0.16735785213879023, 'colsample_bytree': 0.6394617760397262, 'max_depth': 94, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00119	valid-rmse:5.01873
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.875637	valid-rmse:0.903822
[20]	train-rmse:0.363567	valid-rmse:0.411953
[30]	train-rmse:0.332787	valid-rmse:0.38394
[39]	train-rmse:0.328631	valid-rmse:0.380825
Iteration No: 715 ended. Search finished for the next optimal point.
Time taken: 51.0736
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 716 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 155, 'eta': 0.16747444069487732, 'colsample_bytree': 0.64231683467658451, 'max_depth': 95, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00049	valid-rmse:5.01803
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.874622	valid-rmse:0.902752
[20]	train-rmse:0.363268	valid-rmse:0.411488
[30]	train-rmse:0.332904	valid-rmse:0.383602
[39]	train-rmse:0.328602	valid-rmse:0.380509
Iteration No: 716 ended. Search finished for the next optimal point.
Time taken: 51.8044
Function value obtained: 0.3805
Current minimum: 0.3798
Iteration No: 717 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 155, 'eta': 0.16740579377779966, 'colsample_bytree': 0.64182528076139178, 'max_depth': 94, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00091	valid-rmse:5.01844
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.875175	valid-rmse:0.903242
[20]	train-rmse:0.3635	valid-rmse:0.411389
[30]	train-rmse:0.333024	valid-rmse:0.38376
[39]	train-rmse:0.328693	valid-rmse:0.380536
Iteration No: 717 ended. Search finished for the next optimal point.
Time taken: 52.0713
Function value obtained: 0.3805
Current minimum: 0.3798
Iteration No: 718 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 180, 'eta': 0.18204120017423367, 'colsample_bytree': 0.6659246923304778, 'max_depth': 67, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91359	valid-rmse:4.93111
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.748225	valid-rmse:0.778809
[20]	train-rmse:0.351847	valid-rmse:0.40035
[30]	train-rmse:0.333446	valid-rmse:0.383583
[39]	train-rmse:0.329833	valid-rmse:0.3812
Iteration No: 718 ended. Search finished for the next optimal point.
Time taken: 52.2848
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 719 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 130, 'eta': 0.17278263555785725, 'colsample_bytree': 0.73288588416899658, 'max_depth': 80, 'subsample': 1.0, 'lambda': 20.450774955054026, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.97165	valid-rmse:4.98957
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.84506	valid-rmse:0.87445
[20]	train-rmse:0.371807	valid-rmse:0.418196
[30]	train-rmse:0.337288	valid-rmse:0.38647
[39]	train-rmse:0.330725	valid-rmse:0.381394
Iteration No: 719 ended. Search finished for the next optimal point.
Time taken: 48.2990
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 720 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 155, 'eta': 0.16608028819727294, 'colsample_bytree': 0.64026723042228739, 'max_depth': 102, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00882	valid-rmse:5.02636
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.888567	valid-rmse:0.916412
[20]	train-rmse:0.365375	valid-rmse:0.413382
[30]	train-rmse:0.333303	valid-rmse:0.383933
[39]	train-rmse:0.328876	valid-rmse:0.380663
Iteration No: 720 ended. Search finished for the next optimal point.
Time taken: 50.9653
Function value obtained: 0.3807
Current minimum: 0.3798
Iteration No: 721 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 145, 'eta': 0.20264015298092186, 'colsample_bytree': 0.79848684649448431, 'max_depth': 176, 'subsample': 1.0, 'lambda': 55.845508941187589, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.79552	valid-rmse:4.81367
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.64038	valid-rmse:0.674761
[20]	train-rmse:0.35669	valid-rmse:0.403477
[30]	train-rmse:0.337608	valid-rmse:0.386244
[39]	train-rmse:0.331693	valid-rmse:0.38185
Iteration No: 721 ended. Search finished for the next optimal point.
Time taken: 52.1601
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 722 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 145, 'eta': 0.29999999999999999, 'colsample_bytree': 0.68327663577393438, 'max_depth': 168, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21908	valid-rmse:4.23747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.393943	valid-rmse:0.438562
[20]	train-rmse:0.341908	valid-rmse:0.389695
[30]	train-rmse:0.333138	valid-rmse:0.383303
[39]	train-rmse:0.329229	valid-rmse:0.381107
Iteration No: 722 ended. Search finished for the next optimal point.
Time taken: 51.2738
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 723 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.16857777365293036, 'colsample_bytree': 0.71531488280873878, 'max_depth': 161, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99393	valid-rmse:5.0115
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.864006	valid-rmse:0.892263
[20]	train-rmse:0.36258	valid-rmse:0.410415
[30]	train-rmse:0.333786	valid-rmse:0.383611
[39]	train-rmse:0.329631	valid-rmse:0.380588
Iteration No: 723 ended. Search finished for the next optimal point.
Time taken: 53.4087
Function value obtained: 0.3806
Current minimum: 0.3798
Iteration No: 724 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 179, 'eta': 0.18218129701328784, 'colsample_bytree': 0.6637694797727256, 'max_depth': 67, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91275	valid-rmse:4.93028
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.746794	valid-rmse:0.777416
[20]	train-rmse:0.351301	valid-rmse:0.39984
[30]	train-rmse:0.333282	valid-rmse:0.383298
[39]	train-rmse:0.329479	valid-rmse:0.380731
Iteration No: 724 ended. Search finished for the next optimal point.
Time taken: 54.0124
Function value obtained: 0.3807
Current minimum: 0.3798
Iteration No: 725 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.2714231229880561, 'colsample_bytree': 0.75487487730568592, 'max_depth': 170, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.38846	valid-rmse:4.40678
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.424206	valid-rmse:0.46772
[20]	train-rmse:0.343685	valid-rmse:0.391573
[30]	train-rmse:0.333583	valid-rmse:0.383612
[39]	train-rmse:0.329464	valid-rmse:0.381323
Iteration No: 725 ended. Search finished for the next optimal point.
Time taken: 53.9140
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 726 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.16878454216812822, 'colsample_bytree': 0.71458127376653002, 'max_depth': 162, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9927	valid-rmse:5.01026
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.862067	valid-rmse:0.890346
[20]	train-rmse:0.362403	valid-rmse:0.410532
[30]	train-rmse:0.333715	valid-rmse:0.38408
[39]	train-rmse:0.329508	valid-rmse:0.381052
Iteration No: 726 ended. Search finished for the next optimal point.
Time taken: 52.4841
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 727 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.16547160306851483, 'colsample_bytree': 0.64305833461587825, 'max_depth': 110, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01311	valid-rmse:5.03068
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.894645	valid-rmse:0.922193
[20]	train-rmse:0.366793	valid-rmse:0.414414
[30]	train-rmse:0.334122	valid-rmse:0.384272
[39]	train-rmse:0.329384	valid-rmse:0.380892
Iteration No: 727 ended. Search finished for the next optimal point.
Time taken: 53.4096
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 728 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.28033348974839067, 'colsample_bytree': 0.73886127985266659, 'max_depth': 80, 'subsample': 1.0, 'lambda': 42.492194453912575, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.33352	valid-rmse:4.35184
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.407507	valid-rmse:0.451123
[20]	train-rmse:0.34369	valid-rmse:0.390372
[30]	train-rmse:0.33563	valid-rmse:0.38398
[39]	train-rmse:0.33207	valid-rmse:0.381809
Iteration No: 728 ended. Search finished for the next optimal point.
Time taken: 54.2153
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 729 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 71, 'eta': 0.26159142590794315, 'colsample_bytree': 0.68315200545903965, 'max_depth': 98, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.44686	valid-rmse:4.46513
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.441208	valid-rmse:0.483753
[20]	train-rmse:0.343586	valid-rmse:0.392233
[30]	train-rmse:0.332423	valid-rmse:0.383744
[39]	train-rmse:0.327633	valid-rmse:0.381504
Iteration No: 729 ended. Search finished for the next optimal point.
Time taken: 52.0013
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 730 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.16558480198647937, 'colsample_bytree': 0.64320546180322047, 'max_depth': 108, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01178	valid-rmse:5.02932
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.893065	valid-rmse:0.920866
[20]	train-rmse:0.365593	valid-rmse:0.41371
[30]	train-rmse:0.333303	valid-rmse:0.384085
[39]	train-rmse:0.328975	valid-rmse:0.381074
Iteration No: 730 ended. Search finished for the next optimal point.
Time taken: 52.5628
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 731 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 115, 'eta': 0.24366224431084202, 'colsample_bytree': 0.78146373273605652, 'max_depth': 169, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55318	valid-rmse:4.57142
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.481557	valid-rmse:0.522203
[20]	train-rmse:0.347924	valid-rmse:0.395237
[30]	train-rmse:0.334672	valid-rmse:0.384274
[39]	train-rmse:0.329493	valid-rmse:0.380842
Iteration No: 731 ended. Search finished for the next optimal point.
Time taken: 54.2883
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 732 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 114, 'eta': 0.2433861110862561, 'colsample_bytree': 0.77851674778484736, 'max_depth': 169, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55482	valid-rmse:4.57306
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.481452	valid-rmse:0.522245
[20]	train-rmse:0.347073	valid-rmse:0.394858
[30]	train-rmse:0.334214	valid-rmse:0.384236
[39]	train-rmse:0.32923	valid-rmse:0.381124
Iteration No: 732 ended. Search finished for the next optimal point.
Time taken: 54.2334
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 733 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 180, 'eta': 0.18234519723547352, 'colsample_bytree': 0.667548760367488, 'max_depth': 67, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91177	valid-rmse:4.92929
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.745812	valid-rmse:0.776479
[20]	train-rmse:0.351345	valid-rmse:0.399994
[30]	train-rmse:0.333207	valid-rmse:0.383409
[39]	train-rmse:0.329762	valid-rmse:0.381209
Iteration No: 733 ended. Search finished for the next optimal point.
Time taken: 55.1950
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 734 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 156, 'eta': 0.1681851418729669, 'colsample_bytree': 0.64881968091604902, 'max_depth': 91, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.99626	valid-rmse:5.01379
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.867996	valid-rmse:0.896272
[20]	train-rmse:0.362896	valid-rmse:0.410975
[30]	train-rmse:0.333091	valid-rmse:0.383668
[39]	train-rmse:0.328841	valid-rmse:0.380569
Iteration No: 734 ended. Search finished for the next optimal point.
Time taken: 54.4223
Function value obtained: 0.3806
Current minimum: 0.3798
Iteration No: 735 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 160, 'eta': 0.29999999999999999, 'colsample_bytree': 0.72598460643448459, 'max_depth': 94, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21908	valid-rmse:4.23747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.393131	valid-rmse:0.43784
[20]	train-rmse:0.341873	valid-rmse:0.389685
[30]	train-rmse:0.333541	valid-rmse:0.383629
[39]	train-rmse:0.330031	valid-rmse:0.381787
Iteration No: 735 ended. Search finished for the next optimal point.
Time taken: 52.6097
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 736 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 134, 'eta': 0.17896298074209499, 'colsample_bytree': 0.76509634029707074, 'max_depth': 174, 'subsample': 1.0, 'lambda': 31.052871681158642, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93528	valid-rmse:4.95317
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.795624	valid-rmse:0.826
[20]	train-rmse:0.367487	valid-rmse:0.413792
[30]	train-rmse:0.337432	valid-rmse:0.385998
[39]	train-rmse:0.330871	valid-rmse:0.381129
Iteration No: 736 ended. Search finished for the next optimal point.
Time taken: 51.1020
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 737 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 162, 'eta': 0.25819160140653263, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.46666	valid-rmse:4.48491
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.44703	valid-rmse:0.489098
[20]	train-rmse:0.345448	valid-rmse:0.392588
[30]	train-rmse:0.335183	valid-rmse:0.384304
[39]	train-rmse:0.330932	valid-rmse:0.381838
Iteration No: 737 ended. Search finished for the next optimal point.
Time taken: 55.0826
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 738 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 135, 'eta': 0.17910612701437872, 'colsample_bytree': 0.76554041562069508, 'max_depth': 174, 'subsample': 1.0, 'lambda': 31.108105671773711, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93443	valid-rmse:4.95232
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.794486	valid-rmse:0.824881
[20]	train-rmse:0.367663	valid-rmse:0.413804
[30]	train-rmse:0.337662	valid-rmse:0.386208
[39]	train-rmse:0.330943	valid-rmse:0.381038
Iteration No: 738 ended. Search finished for the next optimal point.
Time taken: 51.7886
Function value obtained: 0.3810
Current minimum: 0.3798
Iteration No: 739 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.16936492669366157, 'colsample_bytree': 0.65030087433192985, 'max_depth': 87, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98989	valid-rmse:5.00745
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.857116	valid-rmse:0.885669
[20]	train-rmse:0.361768	valid-rmse:0.409896
[30]	train-rmse:0.333708	valid-rmse:0.384013
[39]	train-rmse:0.329577	valid-rmse:0.381098
Iteration No: 739 ended. Search finished for the next optimal point.
Time taken: 54.3008
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 740 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 99, 'eta': 0.17940771542057118, 'colsample_bytree': 0.70369988284613028, 'max_depth': 68, 'subsample': 1.0, 'lambda': 24.937154356931302, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93242	valid-rmse:4.95034
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.790571	valid-rmse:0.820899
[20]	train-rmse:0.365208	valid-rmse:0.412403
[30]	train-rmse:0.335482	valid-rmse:0.385601
[39]	train-rmse:0.328784	valid-rmse:0.381177
Iteration No: 740 ended. Search finished for the next optimal point.
Time taken: 53.2488
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 741 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 180, 'eta': 0.18241009896002805, 'colsample_bytree': 0.66758109654180486, 'max_depth': 67, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91138	valid-rmse:4.92891
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.745244	valid-rmse:0.775898
[20]	train-rmse:0.351149	valid-rmse:0.399749
[30]	train-rmse:0.332973	valid-rmse:0.383417
[39]	train-rmse:0.329589	valid-rmse:0.381148
Iteration No: 741 ended. Search finished for the next optimal point.
Time taken: 55.5294
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 742 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 158, 'eta': 0.16504030316168969, 'colsample_bytree': 0.64504495426057962, 'max_depth': 121, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01602	valid-rmse:5.03349
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.899598	valid-rmse:0.927091
[20]	train-rmse:0.367576	valid-rmse:0.415119
[30]	train-rmse:0.334639	valid-rmse:0.384689
[39]	train-rmse:0.329792	valid-rmse:0.381273
Iteration No: 742 ended. Search finished for the next optimal point.
Time taken: 53.3008
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 743 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 179, 'eta': 0.22981822913882016, 'colsample_bytree': 0.80406655582905584, 'max_depth': 178, 'subsample': 1.0, 'lambda': 65.209597034210915, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.63441	valid-rmse:4.6526
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.520688	valid-rmse:0.559398
[20]	train-rmse:0.349127	valid-rmse:0.396203
[30]	train-rmse:0.335764	valid-rmse:0.384358
[39]	train-rmse:0.330851	valid-rmse:0.380821
Iteration No: 743 ended. Search finished for the next optimal point.
Time taken: 53.0575
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 744 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 166, 'eta': 0.17154618025466481, 'colsample_bytree': 0.66403798777621859, 'max_depth': 82, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9762	valid-rmse:4.99375
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.836625	valid-rmse:0.865315
[20]	train-rmse:0.359489	valid-rmse:0.407523
[30]	train-rmse:0.333159	valid-rmse:0.38327
[39]	train-rmse:0.329174	valid-rmse:0.380552
Iteration No: 744 ended. Search finished for the next optimal point.
Time taken: 56.1675
Function value obtained: 0.3806
Current minimum: 0.3798
Iteration No: 745 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.1702444879024555, 'colsample_bytree': 0.65322023600874413, 'max_depth': 84, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98464	valid-rmse:5.00221
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.84879	valid-rmse:0.877406
[20]	train-rmse:0.360884	valid-rmse:0.409211
[30]	train-rmse:0.333659	valid-rmse:0.38431
[39]	train-rmse:0.329776	valid-rmse:0.381396
Iteration No: 745 ended. Search finished for the next optimal point.
Time taken: 55.7059
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 746 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 177, 'eta': 0.22838495104133516, 'colsample_bytree': 0.79984707210677508, 'max_depth': 177, 'subsample': 1.0, 'lambda': 65.102910812993059, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.64291	valid-rmse:4.6611
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.525428	valid-rmse:0.563935
[20]	train-rmse:0.349351	valid-rmse:0.396483
[30]	train-rmse:0.335958	valid-rmse:0.384541
[39]	train-rmse:0.331272	valid-rmse:0.381366
Iteration No: 746 ended. Search finished for the next optimal point.
Time taken: 54.1795
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 747 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 166, 'eta': 0.19325144181847906, 'colsample_bytree': 0.75230550636524218, 'max_depth': 61, 'subsample': 1.0, 'lambda': 22.798724537786018, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85	valid-rmse:4.86793
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.689301	valid-rmse:0.721968
[20]	train-rmse:0.356122	valid-rmse:0.403127
[30]	train-rmse:0.335898	valid-rmse:0.384896
[39]	train-rmse:0.330565	valid-rmse:0.381253
Iteration No: 747 ended. Search finished for the next optimal point.
Time taken: 55.8043
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 748 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 147, 'eta': 0.18607036354735063, 'colsample_bytree': 0.78352012715553121, 'max_depth': 177, 'subsample': 1.0, 'lambda': 37.099626540029035, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8933	valid-rmse:4.91142
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.742203	valid-rmse:0.773953
[20]	train-rmse:0.363311	valid-rmse:0.409834
[30]	train-rmse:0.33744	valid-rmse:0.385973
[39]	train-rmse:0.331444	valid-rmse:0.381338
Iteration No: 748 ended. Search finished for the next optimal point.
Time taken: 54.2166
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 749 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.27213421559475615, 'colsample_bytree': 0.75036579750434318, 'max_depth': 169, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.38425	valid-rmse:4.40257
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.422412	valid-rmse:0.466013
[20]	train-rmse:0.342972	valid-rmse:0.391029
[30]	train-rmse:0.333244	valid-rmse:0.383312
[39]	train-rmse:0.329495	valid-rmse:0.381277
Iteration No: 749 ended. Search finished for the next optimal point.
Time taken: 55.9122
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 750 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 103, 'eta': 0.23688805442000685, 'colsample_bytree': 0.77723158728902941, 'max_depth': 167, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.59336	valid-rmse:4.61159
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.500139	valid-rmse:0.540247
[20]	train-rmse:0.348118	valid-rmse:0.395826
[30]	train-rmse:0.334485	valid-rmse:0.384309
[39]	train-rmse:0.329244	valid-rmse:0.380923
Iteration No: 750 ended. Search finished for the next optimal point.
Time taken: 55.2591
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 751 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 106, 'eta': 0.23706657849522561, 'colsample_bytree': 0.77793982629974034, 'max_depth': 168, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.5923	valid-rmse:4.61053
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.499299	valid-rmse:0.539281
[20]	train-rmse:0.347691	valid-rmse:0.395544
[30]	train-rmse:0.33449	valid-rmse:0.384594
[39]	train-rmse:0.329197	valid-rmse:0.381214
Iteration No: 751 ended. Search finished for the next optimal point.
Time taken: 53.7800
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 752 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 160, 'eta': 0.16536206147324087, 'colsample_bytree': 0.65491629537358498, 'max_depth': 125, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01311	valid-rmse:5.03066
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.895488	valid-rmse:0.923054
[20]	train-rmse:0.36645	valid-rmse:0.414262
[30]	train-rmse:0.333371	valid-rmse:0.383892
[39]	train-rmse:0.329038	valid-rmse:0.380647
Iteration No: 752 ended. Search finished for the next optimal point.
Time taken: 55.2765
Function value obtained: 0.3806
Current minimum: 0.3798
Iteration No: 753 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 174, 'eta': 0.16942341686245865, 'colsample_bytree': 0.72184656771906641, 'max_depth': 163, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98889	valid-rmse:5.00643
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.855765	valid-rmse:0.884256
[20]	train-rmse:0.361661	valid-rmse:0.41006
[30]	train-rmse:0.333744	valid-rmse:0.384102
[39]	train-rmse:0.32979	valid-rmse:0.381436
Iteration No: 753 ended. Search finished for the next optimal point.
Time taken: 55.6874
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 754 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 157, 'eta': 0.17574798182673051, 'colsample_bytree': 0.75430029968228784, 'max_depth': 73, 'subsample': 1.0, 'lambda': 20.753126331112828, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95403	valid-rmse:4.97196
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.819856	valid-rmse:0.849746
[20]	train-rmse:0.36896	valid-rmse:0.415291
[30]	train-rmse:0.337524	valid-rmse:0.386243
[39]	train-rmse:0.331061	valid-rmse:0.381222
Iteration No: 754 ended. Search finished for the next optimal point.
Time taken: 55.1730
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 755 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 181, 'eta': 0.22631285426362852, 'colsample_bytree': 0.80844063887143869, 'max_depth': 200, 'subsample': 1.0, 'lambda': 64.269760050352758, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.65519	valid-rmse:4.67338
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.533049	valid-rmse:0.57126
[20]	train-rmse:0.350693	valid-rmse:0.397679
[30]	train-rmse:0.336279	valid-rmse:0.38486
[39]	train-rmse:0.331354	valid-rmse:0.381317
Iteration No: 755 ended. Search finished for the next optimal point.
Time taken: 54.5705
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 756 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 173, 'eta': 0.16922062218226805, 'colsample_bytree': 0.7188151695544156, 'max_depth': 163, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9901	valid-rmse:5.00765
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.858463	valid-rmse:0.886729
[20]	train-rmse:0.362351	valid-rmse:0.410404
[30]	train-rmse:0.334087	valid-rmse:0.38407
[39]	train-rmse:0.33	valid-rmse:0.381148
Iteration No: 756 ended. Search finished for the next optimal point.
Time taken: 57.5093
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 757 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 192, 'eta': 0.23896341418471018, 'colsample_bytree': 0.80711253541021355, 'max_depth': 176, 'subsample': 1.0, 'lambda': 65.239372103855615, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.58012	valid-rmse:4.59833
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.491517	valid-rmse:0.531477
[20]	train-rmse:0.347595	valid-rmse:0.394269
[30]	train-rmse:0.335335	valid-rmse:0.383979
[39]	train-rmse:0.331077	valid-rmse:0.381149
Iteration No: 757 ended. Search finished for the next optimal point.
Time taken: 54.0992
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 758 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 158, 'eta': 0.16534597571955331, 'colsample_bytree': 0.65438166262091635, 'max_depth': 117, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.01419	valid-rmse:5.03167
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.896596	valid-rmse:0.92393
[20]	train-rmse:0.367561	valid-rmse:0.414948
[30]	train-rmse:0.33526	valid-rmse:0.385292
[39]	train-rmse:0.330645	valid-rmse:0.381828
Iteration No: 758 ended. Search finished for the next optimal point.
Time taken: 56.4919
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 759 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 184, 'eta': 0.18536796028649583, 'colsample_bytree': 0.66925165124081432, 'max_depth': 65, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89372	valid-rmse:4.91124
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.722575	valid-rmse:0.753831
[20]	train-rmse:0.349658	valid-rmse:0.398048
[30]	train-rmse:0.332718	valid-rmse:0.382844
[39]	train-rmse:0.329349	valid-rmse:0.380545
Iteration No: 759 ended. Search finished for the next optimal point.
Time taken: 55.3938
Function value obtained: 0.3805
Current minimum: 0.3798
Iteration No: 760 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 208, 'eta': 0.24099818436692402, 'colsample_bytree': 1.0, 'max_depth': 172, 'subsample': 1.0, 'lambda': 62.503826179818105, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.56776	valid-rmse:4.58601
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.484695	valid-rmse:0.524634
[20]	train-rmse:0.347239	valid-rmse:0.393988
[30]	train-rmse:0.335842	valid-rmse:0.384484
[39]	train-rmse:0.331805	valid-rmse:0.381937
Iteration No: 760 ended. Search finished for the next optimal point.
Time taken: 58.7171
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 761 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 133, 'eta': 0.2728872870025989, 'colsample_bytree': 0.74770760534696623, 'max_depth': 170, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.37978	valid-rmse:4.39811
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.422242	valid-rmse:0.465849
[20]	train-rmse:0.343185	valid-rmse:0.391488
[30]	train-rmse:0.333446	valid-rmse:0.383898
[39]	train-rmse:0.329258	valid-rmse:0.381647
Iteration No: 761 ended. Search finished for the next optimal point.
Time taken: 57.4973
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 762 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 164, 'eta': 0.19317175096857325, 'colsample_bytree': 0.75028242257354272, 'max_depth': 61, 'subsample': 1.0, 'lambda': 22.968803007388129, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.85048	valid-rmse:4.86841
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.690313	valid-rmse:0.722763
[20]	train-rmse:0.356378	valid-rmse:0.402776
[30]	train-rmse:0.335698	valid-rmse:0.384114
[39]	train-rmse:0.330695	valid-rmse:0.380652
Iteration No: 762 ended. Search finished for the next optimal point.
Time taken: 55.8787
Function value obtained: 0.3807
Current minimum: 0.3798
Iteration No: 763 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 127, 'eta': 0.22937565217410644, 'colsample_bytree': 1.0, 'max_depth': 78, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.63762	valid-rmse:4.65583
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.523881	valid-rmse:0.56265
[20]	train-rmse:0.349225	valid-rmse:0.39676
[30]	train-rmse:0.335788	valid-rmse:0.385201
[39]	train-rmse:0.330658	valid-rmse:0.38199
Iteration No: 763 ended. Search finished for the next optimal point.
Time taken: 59.5006
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 764 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 92, 'eta': 0.22788485127878946, 'colsample_bytree': 0.80121289994979916, 'max_depth': 168, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.64677	valid-rmse:4.66498
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.530005	valid-rmse:0.568685
[20]	train-rmse:0.349196	valid-rmse:0.396955
[30]	train-rmse:0.334567	valid-rmse:0.384649
[39]	train-rmse:0.329385	valid-rmse:0.381484
Iteration No: 764 ended. Search finished for the next optimal point.
Time taken: 56.9427
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 765 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 188, 'eta': 0.18462453570023718, 'colsample_bytree': 0.67855297343131049, 'max_depth': 66, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89816	valid-rmse:4.91568
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.728698	valid-rmse:0.759544
[20]	train-rmse:0.350141	valid-rmse:0.398391
[30]	train-rmse:0.333201	valid-rmse:0.383026
[39]	train-rmse:0.329624	valid-rmse:0.380744
Iteration No: 765 ended. Search finished for the next optimal point.
Time taken: 58.7846
Function value obtained: 0.3807
Current minimum: 0.3798
Iteration No: 766 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 189, 'eta': 0.18445638009806703, 'colsample_bytree': 0.6807917145705451, 'max_depth': 66, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89916	valid-rmse:4.91668
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.729607	valid-rmse:0.76053
[20]	train-rmse:0.350235	valid-rmse:0.398697
[30]	train-rmse:0.33301	valid-rmse:0.383084
[39]	train-rmse:0.329655	valid-rmse:0.380893
Iteration No: 766 ended. Search finished for the next optimal point.
Time taken: 57.6721
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 767 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 187, 'eta': 0.18431610348211083, 'colsample_bytree': 0.67800243919424052, 'max_depth': 66, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9	valid-rmse:4.91752
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.730397	valid-rmse:0.761251
[20]	train-rmse:0.350151	valid-rmse:0.398412
[30]	train-rmse:0.33286	valid-rmse:0.38283
[39]	train-rmse:0.329358	valid-rmse:0.380603
Iteration No: 767 ended. Search finished for the next optimal point.
Time taken: 59.3901
Function value obtained: 0.3806
Current minimum: 0.3798
Iteration No: 768 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 162, 'eta': 0.19333138565800573, 'colsample_bytree': 0.75065380416736716, 'max_depth': 61, 'subsample': 1.0, 'lambda': 23.345374790215704, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84955	valid-rmse:4.86748
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.68872	valid-rmse:0.721265
[20]	train-rmse:0.355986	valid-rmse:0.402643
[30]	train-rmse:0.335713	valid-rmse:0.384347
[39]	train-rmse:0.330686	valid-rmse:0.380974
Iteration No: 768 ended. Search finished for the next optimal point.
Time taken: 58.3078
Function value obtained: 0.3810
Current minimum: 0.3798
Iteration No: 769 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 138, 'eta': 0.26132117373606667, 'colsample_bytree': 0.76765948702146103, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.44836	valid-rmse:4.46666
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.44219	valid-rmse:0.484347
[20]	train-rmse:0.345426	valid-rmse:0.392686
[30]	train-rmse:0.334167	valid-rmse:0.383671
[39]	train-rmse:0.329792	valid-rmse:0.380906
Iteration No: 769 ended. Search finished for the next optimal point.
Time taken: 56.6640
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 770 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 148, 'eta': 0.17582040559941642, 'colsample_bytree': 0.63606171502815956, 'max_depth': 73, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.95206	valid-rmse:4.96953
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.798896	valid-rmse:0.828639
[20]	train-rmse:0.354692	valid-rmse:0.403735
[30]	train-rmse:0.332401	valid-rmse:0.383376
[39]	train-rmse:0.328621	valid-rmse:0.380922
Iteration No: 770 ended. Search finished for the next optimal point.
Time taken: 60.1868
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 771 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 193, 'eta': 0.18460341908146111, 'colsample_bytree': 0.68674102603466303, 'max_depth': 66, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.89829	valid-rmse:4.91581
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.728943	valid-rmse:0.759956
[20]	train-rmse:0.350798	valid-rmse:0.399244
[30]	train-rmse:0.333748	valid-rmse:0.383688
[39]	train-rmse:0.330221	valid-rmse:0.381244
Iteration No: 771 ended. Search finished for the next optimal point.
Time taken: 58.7407
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 772 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.29999999999999999, 'colsample_bytree': 0.73276423582923478, 'max_depth': 83, 'subsample': 1.0, 'lambda': 49.948365015748244, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21716	valid-rmse:4.23554
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.389687	valid-rmse:0.434141
[20]	train-rmse:0.343156	valid-rmse:0.389645
[30]	train-rmse:0.335286	valid-rmse:0.383883
[39]	train-rmse:0.332327	valid-rmse:0.382171
Iteration No: 772 ended. Search finished for the next optimal point.
Time taken: 57.4684
Function value obtained: 0.3822
Current minimum: 0.3798
Iteration No: 773 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 128, 'eta': 0.27404589722782025, 'colsample_bytree': 0.73153536700227662, 'max_depth': 91, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.37302	valid-rmse:4.39133
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.420825	valid-rmse:0.46426
[20]	train-rmse:0.343002	valid-rmse:0.390947
[30]	train-rmse:0.333348	valid-rmse:0.383558
[39]	train-rmse:0.32905	valid-rmse:0.381425
Iteration No: 773 ended. Search finished for the next optimal point.
Time taken: 56.2387
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 774 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 11, 'eta': 0.24406500967412828, 'colsample_bytree': 0.43115043036392509, 'max_depth': 199, 'subsample': 0.82514108498155159, 'lambda': 83.363208732617338, 'gamma': 2, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.55111	valid-rmse:4.56949
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.486678	valid-rmse:0.527522
[20]	train-rmse:0.355707	valid-rmse:0.402349
[30]	train-rmse:0.343475	valid-rmse:0.391044
[39]	train-rmse:0.339752	valid-rmse:0.388082
Iteration No: 774 ended. Search finished for the next optimal point.
Time taken: 53.6788
Function value obtained: 0.3881
Current minimum: 0.3798
Iteration No: 775 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 198, 'eta': 0.18310741153223473, 'colsample_bytree': 0.69866401595732208, 'max_depth': 67, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.90721	valid-rmse:4.92474
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.740185	valid-rmse:0.770997
[20]	train-rmse:0.351556	valid-rmse:0.399759
[30]	train-rmse:0.333787	valid-rmse:0.383637
[39]	train-rmse:0.330332	valid-rmse:0.381362
Iteration No: 775 ended. Search finished for the next optimal point.
Time taken: 58.6865
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 776 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 142, 'eta': 0.27663002775826329, 'colsample_bytree': 0.75767098093347984, 'max_depth': 170, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.35759	valid-rmse:4.37593
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.416513	valid-rmse:0.46003
[20]	train-rmse:0.344073	valid-rmse:0.391849
[30]	train-rmse:0.333979	valid-rmse:0.383814
[39]	train-rmse:0.330038	valid-rmse:0.38142
Iteration No: 776 ended. Search finished for the next optimal point.
Time taken: 56.0431
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 777 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 172, 'eta': 0.16945710012754781, 'colsample_bytree': 0.72636679394277381, 'max_depth': 166, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98869	valid-rmse:5.00624
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.855851	valid-rmse:0.884302
[20]	train-rmse:0.36202	valid-rmse:0.410214
[30]	train-rmse:0.333796	valid-rmse:0.384219
[39]	train-rmse:0.329887	valid-rmse:0.381484
Iteration No: 777 ended. Search finished for the next optimal point.
Time taken: 59.7276
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 778 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 130, 'eta': 0.17175276783340715, 'colsample_bytree': 0.61487859347085194, 'max_depth': 80, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.975	valid-rmse:4.99257
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.834748	valid-rmse:0.863751
[20]	train-rmse:0.358238	valid-rmse:0.407525
[30]	train-rmse:0.332183	valid-rmse:0.383883
[39]	train-rmse:0.328505	valid-rmse:0.381488
Iteration No: 778 ended. Search finished for the next optimal point.
Time taken: 59.6795
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 779 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 160, 'eta': 0.29999999999999999, 'colsample_bytree': 0.72386140706190616, 'max_depth': 95, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21908	valid-rmse:4.23747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.393131	valid-rmse:0.43784
[20]	train-rmse:0.341873	valid-rmse:0.389685
[30]	train-rmse:0.333541	valid-rmse:0.383629
[39]	train-rmse:0.330031	valid-rmse:0.381787
Iteration No: 779 ended. Search finished for the next optimal point.
Time taken: 59.5108
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 780 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 171, 'eta': 0.16993704556007716, 'colsample_bytree': 0.6730268299606863, 'max_depth': 88, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98582	valid-rmse:5.00338
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.852137	valid-rmse:0.880555
[20]	train-rmse:0.361734	valid-rmse:0.409673
[30]	train-rmse:0.333914	valid-rmse:0.384047
[39]	train-rmse:0.329825	valid-rmse:0.381229
Iteration No: 780 ended. Search finished for the next optimal point.
Time taken: 60.1287
Function value obtained: 0.3812
Current minimum: 0.3798
Iteration No: 781 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 124, 'eta': 0.22609957533699684, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.65706	valid-rmse:4.67526
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.535318	valid-rmse:0.573608
[20]	train-rmse:0.350493	valid-rmse:0.398044
[30]	train-rmse:0.335828	valid-rmse:0.385332
[39]	train-rmse:0.330563	valid-rmse:0.38185
Iteration No: 781 ended. Search finished for the next optimal point.
Time taken: 60.4692
Function value obtained: 0.3819
Current minimum: 0.3798
Iteration No: 782 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 139, 'eta': 0.19867925921897989, 'colsample_bytree': 0.79616033143223475, 'max_depth': 175, 'subsample': 1.0, 'lambda': 53.553392208784565, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.8189	valid-rmse:4.83705
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.661803	valid-rmse:0.695729
[20]	train-rmse:0.357469	valid-rmse:0.404404
[30]	train-rmse:0.337249	valid-rmse:0.385989
[39]	train-rmse:0.331132	valid-rmse:0.381301
Iteration No: 782 ended. Search finished for the next optimal point.
Time taken: 59.7051
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 783 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 103, 'eta': 0.18264759891086985, 'colsample_bytree': 0.7166457851325202, 'max_depth': 65, 'subsample': 1.0, 'lambda': 27.686718308893866, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91325	valid-rmse:4.93114
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.765652	valid-rmse:0.796667
[20]	train-rmse:0.363016	valid-rmse:0.410323
[30]	train-rmse:0.335549	valid-rmse:0.385234
[39]	train-rmse:0.329043	valid-rmse:0.380661
Iteration No: 783 ended. Search finished for the next optimal point.
Time taken: 58.3905
Function value obtained: 0.3807
Current minimum: 0.3798
Iteration No: 784 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 152, 'eta': 0.19378476248574633, 'colsample_bytree': 0.75508619630726481, 'max_depth': 61, 'subsample': 1.0, 'lambda': 27.081692520149218, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84699	valid-rmse:4.86489
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.68677	valid-rmse:0.719627
[20]	train-rmse:0.356289	valid-rmse:0.402958
[30]	train-rmse:0.335716	valid-rmse:0.384437
[39]	train-rmse:0.330524	valid-rmse:0.380892
Iteration No: 784 ended. Search finished for the next optimal point.
Time taken: 58.9787
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 785 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 185, 'eta': 0.18606237005234572, 'colsample_bytree': 0.67269814712124454, 'max_depth': 65, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.88958	valid-rmse:4.90709
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.717373	valid-rmse:0.748742
[20]	train-rmse:0.349304	valid-rmse:0.397837
[30]	train-rmse:0.332939	valid-rmse:0.383082
[39]	train-rmse:0.329639	valid-rmse:0.380937
Iteration No: 785 ended. Search finished for the next optimal point.
Time taken: 60.0413
Function value obtained: 0.3809
Current minimum: 0.3798
Iteration No: 786 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 101, 'eta': 0.1817361910213596, 'colsample_bytree': 0.71346032621143241, 'max_depth': 66, 'subsample': 1.0, 'lambda': 27.095484442385079, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.91865	valid-rmse:4.93654
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.772565	valid-rmse:0.803396
[20]	train-rmse:0.363185	valid-rmse:0.410614
[30]	train-rmse:0.335511	valid-rmse:0.385468
[39]	train-rmse:0.328802	valid-rmse:0.380812
Iteration No: 786 ended. Search finished for the next optimal point.
Time taken: 56.3060
Function value obtained: 0.3808
Current minimum: 0.3798
Iteration No: 787 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 300, 'eta': 0.26733138775559284, 'colsample_bytree': 0.79802813007540863, 'max_depth': 200, 'subsample': 1.0, 'lambda': 39.2324796727058, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.41057	valid-rmse:4.42886
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.42589	valid-rmse:0.468531
[20]	train-rmse:0.344554	valid-rmse:0.390925
[30]	train-rmse:0.335926	valid-rmse:0.383917
[39]	train-rmse:0.332418	valid-rmse:0.381641
Iteration No: 787 ended. Search finished for the next optimal point.
Time taken: 61.6746
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 788 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 155, 'eta': 0.19416311622631213, 'colsample_bytree': 0.75819310442225407, 'max_depth': 61, 'subsample': 1.0, 'lambda': 26.974656761455545, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.84474	valid-rmse:4.86265
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.684393	valid-rmse:0.717357
[20]	train-rmse:0.356179	valid-rmse:0.403064
[30]	train-rmse:0.335826	valid-rmse:0.384788
[39]	train-rmse:0.330534	valid-rmse:0.381538
Iteration No: 788 ended. Search finished for the next optimal point.
Time taken: 57.2606
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 789 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 172, 'eta': 0.16938732970694612, 'colsample_bytree': 0.72873025539507386, 'max_depth': 165, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9891	valid-rmse:5.00666
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.856528	valid-rmse:0.885005
[20]	train-rmse:0.362006	valid-rmse:0.410222
[30]	train-rmse:0.334137	valid-rmse:0.384707
[39]	train-rmse:0.329853	valid-rmse:0.381624
Iteration No: 789 ended. Search finished for the next optimal point.
Time taken: 61.1641
Function value obtained: 0.3816
Current minimum: 0.3798
Iteration No: 790 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 162, 'eta': 0.17038817327727998, 'colsample_bytree': 1.0, 'max_depth': 76, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.98309	valid-rmse:5.00064
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.846745	valid-rmse:0.875451
[20]	train-rmse:0.360598	valid-rmse:0.409372
[30]	train-rmse:0.334	valid-rmse:0.385017
[39]	train-rmse:0.330188	valid-rmse:0.382462
Iteration No: 790 ended. Search finished for the next optimal point.
Time taken: 73.8325
Function value obtained: 0.3825
Current minimum: 0.3798
Iteration No: 791 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 99, 'eta': 0.17975917852645296, 'colsample_bytree': 0.70566139340831824, 'max_depth': 68, 'subsample': 1.0, 'lambda': 25.521354626811839, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.93035	valid-rmse:4.94827
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.78811	valid-rmse:0.818727
[20]	train-rmse:0.365191	valid-rmse:0.412634
[30]	train-rmse:0.335967	valid-rmse:0.386369
[39]	train-rmse:0.329504	valid-rmse:0.381774
Iteration No: 791 ended. Search finished for the next optimal point.
Time taken: 61.5829
Function value obtained: 0.3818
Current minimum: 0.3798
Iteration No: 792 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 148, 'eta': 0.29999999999999999, 'colsample_bytree': 0.68688740612207067, 'max_depth': 170, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.21908	valid-rmse:4.23747
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.393857	valid-rmse:0.438409
[20]	train-rmse:0.341909	valid-rmse:0.389839
[30]	train-rmse:0.333094	valid-rmse:0.383432
[39]	train-rmse:0.329564	valid-rmse:0.381485
Iteration No: 792 ended. Search finished for the next optimal point.
Time taken: 61.8673
Function value obtained: 0.3815
Current minimum: 0.3798
Iteration No: 793 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 132, 'eta': 0.18104552241439564, 'colsample_bytree': 0.77171026580433433, 'max_depth': 175, 'subsample': 1.0, 'lambda': 34.400195647664511, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.9231	valid-rmse:4.94121
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.779886	valid-rmse:0.810695
[20]	train-rmse:0.366672	valid-rmse:0.413306
[30]	train-rmse:0.337372	valid-rmse:0.386296
[39]	train-rmse:0.330869	valid-rmse:0.381378
Iteration No: 793 ended. Search finished for the next optimal point.
Time taken: 59.3698
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 794 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 160, 'eta': 0.16589083380324054, 'colsample_bytree': 0.65974570281043121, 'max_depth': 116, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:5.00994	valid-rmse:5.0275
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.89046	valid-rmse:0.918232
[20]	train-rmse:0.366293	valid-rmse:0.414127
[30]	train-rmse:0.33421	valid-rmse:0.384589
[39]	train-rmse:0.32975	valid-rmse:0.381304
Iteration No: 794 ended. Search finished for the next optimal point.
Time taken: 62.6343
Function value obtained: 0.3813
Current minimum: 0.3798
Iteration No: 795 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 127, 'eta': 0.17310552347857378, 'colsample_bytree': 0.58784310621592328, 'max_depth': 77, 'subsample': 1.0, 'lambda': 0.10000000000000001, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.96699	valid-rmse:4.98453
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.821753	valid-rmse:0.851186
[20]	train-rmse:0.356101	valid-rmse:0.405807
[30]	train-rmse:0.331628	valid-rmse:0.38352
[39]	train-rmse:0.327798	valid-rmse:0.380954
Iteration No: 795 ended. Search finished for the next optimal point.
Time taken: 62.7676
Function value obtained: 0.3810
Current minimum: 0.3798
Iteration No: 796 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 170, 'eta': 0.24834426187830611, 'colsample_bytree': 0.77383737912122741, 'max_depth': 86, 'subsample': 1.0, 'lambda': 58.906577883538709, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.52423	valid-rmse:4.54246
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.464814	valid-rmse:0.50584
[20]	train-rmse:0.345814	valid-rmse:0.392826
[30]	train-rmse:0.334654	valid-rmse:0.383546
[39]	train-rmse:0.330353	valid-rmse:0.380984
Iteration No: 796 ended. Search finished for the next optimal point.
Time taken: 62.4793
Function value obtained: 0.3810
Current minimum: 0.3798
Iteration No: 797 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 72, 'eta': 0.2570899097226641, 'colsample_bytree': 0.71280845518629699, 'max_depth': 103, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.47355	valid-rmse:4.49182
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.450003	valid-rmse:0.492421
[20]	train-rmse:0.343981	valid-rmse:0.392635
[30]	train-rmse:0.332352	valid-rmse:0.38399
[39]	train-rmse:0.327355	valid-rmse:0.381387
Iteration No: 797 ended. Search finished for the next optimal point.
Time taken: 58.1514
Function value obtained: 0.3814
Current minimum: 0.3798
Iteration No: 798 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 179, 'eta': 0.17990512771427042, 'colsample_bytree': 0.77562287271664321, 'max_depth': 69, 'subsample': 1.0, 'lambda': 21.049980701039953, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.92932	valid-rmse:4.94724
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.785763	valid-rmse:0.816231
[20]	train-rmse:0.365276	valid-rmse:0.411694
[30]	train-rmse:0.337287	valid-rmse:0.385725
[39]	train-rmse:0.331229	valid-rmse:0.381124
Iteration No: 798 ended. Search finished for the next optimal point.
Time taken: 59.5721
Function value obtained: 0.3811
Current minimum: 0.3798
Iteration No: 799 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 98, 'eta': 0.25332343208087205, 'colsample_bytree': 0.77109968133095608, 'max_depth': 133, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.49589	valid-rmse:4.51414
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.458027	valid-rmse:0.500231
[20]	train-rmse:0.346147	valid-rmse:0.394573
[30]	train-rmse:0.333876	valid-rmse:0.384842
[39]	train-rmse:0.328751	valid-rmse:0.381955
Iteration No: 799 ended. Search finished for the next optimal point.
Time taken: 60.4233
Function value obtained: 0.3820
Current minimum: 0.3798
Iteration No: 800 started. Searching for the next optimal point.

Next set of params..... {'min_child_weight': 167, 'eta': 0.26122138782936311, 'colsample_bytree': 1.0, 'max_depth': 200, 'subsample': 1.0, 'lambda': 90.0, 'gamma': 0, 'nthread': 8, 'booster': 'gbtree', 'silent': 1, 'eval_metric': 'rmse', 'objective': 'reg:linear'}
[0]	train-rmse:4.4487	valid-rmse:4.46696
Multiple eval metrics have been passed: 'valid-rmse' will be used for early stopping.

Will train until valid-rmse hasn't improved in 50 rounds.
[10]	train-rmse:0.440733	valid-rmse:0.482894
[20]	train-rmse:0.345128	valid-rmse:0.392153
[30]	train-rmse:0.335195	valid-rmse:0.384017
[39]	train-rmse:0.331026	valid-rmse:0.381611
Iteration No: 800 ended. Search finished for the next optimal point.
Time taken: 15.8990
Function value obtained: 0.3816
Current minimum: 0.3798
CPU times: user 1d 45min 19s, sys: 1h 33min 23s, total: 1d 2h 18min 42s
Wall time: 6h 30min 17s

In [148]:
print('Best Params=',result.x)
print('Best Score=',result.fun)
from skopt.plots import plot_convergence
_ = plt.figure(figsize=(18,6))
_ = plot_convergence(result, yscale='log')


Best Params= [133, 0.17936020611338641, 0.70459161599199072, 64, 1.0, 24.2701922969149, 0]
Best Score= 0.379799721793

XGBoost model hyperparameter search - RandomSearch with cutdown data


In [ ]:
%%time
# XGBoost with Randomized search and 5-fold CV

# Tuning Approach
# set all params to default (incl learning rate=0.1)
# tune min_child_weight and max_depth together for [1,2,3,4,5,6]
# tune gamma from 0-1
# tune subsample and colsample_bytree around 0.5-1
# tune reg_alpha, reg_lambda from 0-20

import xgboost as xgb
from sklearn.model_selection import RandomizedSearchCV, GridSearchCV
from sklearn.metrics import mean_squared_error

params = {
      'learning_rate':    np.linspace(0.05, 0.22, 10),
      'min_child_weight': np.linspace(50, 90, 10).astype(int), 
      'max_depth':        np.linspace(10, 80, 10).astype(int), 
      'gamma':            np.linspace(0, 0.1, 3), 
      'subsample':        np.linspace(0.5, 0.8, 5), 
      'colsample_bytree': np.linspace(0.3, 1, 8), 
      'reg_alpha':        np.linspace(0, 2, 5), 
      'reg_lambda':       np.linspace(0, 45, 5),
}

XGBmodel = xgb.XGBRegressor(base_score=np.mean(ytrain_small), n_estimators=100, eval_metric='rmse', 
                            random_state=1, n_jobs=1)
                            
# XGBmodel = GridSearchCV(XGBmodel, cv=5, param_grid=params, verbose=2)
XGBmodel = RandomizedSearchCV(XGBmodel, cv=5, n_iter=500, n_jobs=-1, param_distributions=params, verbose=1, random_state=1)
XGBmodel.fit(Xtrain_small, ytrain_small)
print(XGBmodel.best_estimator_)
print(XGBmodel.best_params_)

XGBtrain_preds = XGBmodel.predict(Xtrain_small)
XGBvalid_preds = XGBmodel.predict(Xvalid)
print('\nTotal training size',len(Xtrain_small))
print('Train  RMSE =', round(np.sqrt(mean_squared_error(ytrain_small, XGBtrain_preds)),6))
print('Validn RMSE =', round(np.sqrt(mean_squared_error(yvalid, XGBvalid_preds)),6))

In [ ]:
feature_importance = pd.Series(index = Xtrain.columns, data = XGBmodel.best_estimator_.feature_importances_)
_ = feature_importance.sort_values(ascending=False).head(30).plot(kind='bar', color="r", figsize = (18,6))

In [ ]:
XGBlog_test_preds = XGBmodel.predict(Xtest)
XGBtest_preds = np.exp(XGBlog_test_preds) - 1
XGBpreds = pd.DataFrame({'id': test_id, 'trip_duration': XGBtest_preds})
XGBpreds.to_csv('XG_tuned_submission.csv.gz', index=False, compression='gzip')

Ridge Regression

Works very poorly as larger values of distance_great_circle cause massive increases in duration predictions


In [ ]:
%%time
from sklearn.linear_model import RidgeCV, Ridge
from sklearn.metrics import mean_squared_error

# use CV to find best alpha on train data, then just plug into Ridge call below for faster runtime
#alphas = np.linspace(0.1, 5, 10)
#RRmodel = RidgeCV(cv=5, alphas=alphas, scoring='neg_mean_squared_error')

RRmodel = Ridge(alpha=2, random_state=1)
RRmodel.fit(Xtrain, ytrain)
RRtrain_preds = RRmodel.predict(Xtrain)
RRvalid_preds = RRmodel.predict(Xvalid)

RRtrain_score = round(np.sqrt(mean_squared_error(ytrain, RRtrain_preds)),6)
RRvalid_score = round(np.sqrt(mean_squared_error(yvalid, RRvalid_preds)),6)
print('Train RMSE =', RRtrain_score)
print('Test  RMSE =', RRvalid_score)
#RRmodel.alphas
#RRmodel.alpha_

# plot feature importances
feature_importance = pd.Series(index = Xtrain.columns, data = np.abs(RRmodel.coef_))
_ = feature_importance.sort_values(ascending=False).head(30).plot(kind='bar', color="r", figsize = (18,6))

In [ ]:
# create Ridge Regression file for submission
RRlog_test_preds = RRmodel.predict(Xtest)
RRtest_preds = np.abs(np.exp(RRlog_test_preds)-1)
RRpreds = pd.DataFrame({'id': test_id, 'trip_duration': RRtest_preds})
RRpreds.to_csv('RR_submission.csv.gz', index=False, compression='gzip')
print('File created')

In [ ]:
# show ridge coefficients as a function of regularisation
alphas = np.logspace(-3, 9, 15)
coefs = []
for a in alphas:
    ridge = Ridge(alpha=a, fit_intercept=False)
    _ = ridge.fit(Xtrain, ytrain)
    coefs.append(ridge.coef_)

_ = plt.figure(figsize=(18,6))
ax = plt.gca()
_ = ax.plot(alphas, coefs)
_ = ax.set_xscale('log')
_ = ax.set_xlim(ax.get_xlim()[::-1])  # reverse axis
_ = plt.xlabel('alpha')
_ = plt.ylabel('weights')
_ = plt.title('Ridge coefficients as a function of l2 regularization')

In [ ]:
# check the largest prediction record and calculate to see where overestimate is
# problem is distance_great_circle which distorts predictions for large distances
index = RRvalid_preds.argmax()
row = Xvalid.iloc[index]
result = RRmodel.intercept_
print('Intercept= ', round(result,4))
for name, item, coef in zip(feature_names, row, RRmodel.coef_):
    print('{0:25} {1:9} * {2:9} = {3:9}'.format(name, round(coef,4), round(np.float(item),4), 
                                                round(np.float(item) * coef,4)))
    result = result + np.float(item) * coef
    
print('\nPrediction= {0}, calculated result using coefficients= {1}'.format(RRvalid_preds[index], result))
Xv = scaler.inverse_transform(Xvalid)

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