To understand the factors that lead a person to look for a job change, the agency wants you to design a model that uses the current credentials/demographics/experience to predict the probability of an enrollee to look for a new job.
Data Dictionary
Variable Description
In [1]:
%load_ext autoreload
%autoreload 2
%matplotlib inline
In [2]:
import time
import xgboost as xgb
import lightgbm as lgb
import category_encoders as cat_ed
import gc, mlcrate, glob
from fastai.imports import *
from fastai.structured import *
from gplearn.genetic import SymbolicTransformer
from pandas_summary import DataFrameSummary
from sklearn.ensemble import RandomForestClassifier, ExtraTreesClassifier
from IPython.display import display
from catboost import CatBoostClassifier
from scipy.cluster import hierarchy as hc
from collections import Counter
from mlxtend.feature_selection import SequentialFeatureSelector as SFS
from sklearn import metrics
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import train_test_split
from sklearn.metrics import mean_squared_error
from sklearn.metrics import roc_auc_score, log_loss
from sklearn.model_selection import KFold, StratifiedKFold
from sklearn.model_selection import GridSearchCV
from sklearn.decomposition import PCA, TruncatedSVD, FastICA, FactorAnalysis
from sklearn.random_projection import GaussianRandomProjection, SparseRandomProjection
from sklearn.cluster import KMeans
from sklearn.metrics import accuracy_score, log_loss
from sklearn.neighbors import KNeighborsClassifier
from sklearn.tree import DecisionTreeClassifier
from sklearn.ensemble import AdaBoostClassifier, GradientBoostingClassifier
from sklearn.naive_bayes import GaussianNB
from sklearn.discriminant_analysis import QuadraticDiscriminantAnalysis
from sklearn.neural_network import MLPClassifier
from sklearn.gaussian_process import GaussianProcessClassifier
from sklearn.gaussian_process.kernels import RBF
# will ignore all warning from sklearn, seaborn etc..
def ignore_warn(*args, **kwargs):
pass
warnings.warn = ignore_warn
pd.option_context("display.max_rows", 1000);
pd.option_context("display.max_columns", 1000);
In [3]:
PATH = os.getcwd();
PATH
Out[3]:
'D:\\Github\\fastai\\courses\\ml1'
In [11]:
df_raw = pd.read_csv(f'{PATH}\\AV_Stud_2\\train.csv', low_memory=False)
df_test = pd.read_csv(f'{PATH}\\AV_Stud_2\\test.csv', low_memory=False)
# STEM - Science, Technology, Engineering, Management
In [12]:
def display_all(df):
with pd.option_context("display.max_rows", 100):
with pd.option_context("display.max_columns", 100):
display(df)
In [13]:
df_raw.shape,
Out[13]:
((18359, 14),)
In [14]:
df_raw.get_ftype_counts()
Out[14]:
float64:dense 1
int64:dense 3
object:dense 10
dtype: int64
In [40]:
m = RandomForestRegressor(n_jobs=-1)
m.fit(df_raw.drop('target', axis=1), df_raw.target)
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-40-e7e89172fae8> in <module>()
1 m = RandomForestRegressor(n_jobs=-1)
----> 2 m.fit(df_raw.drop('target', axis=1), df_raw.target)
C:\ProgramData\Anaconda3\lib\site-packages\sklearn\ensemble\forest.py in fit(self, X, y, sample_weight)
245 """
246 # Validate or convert input data
--> 247 X = check_array(X, accept_sparse="csc", dtype=DTYPE)
248 y = check_array(y, accept_sparse='csc', ensure_2d=False, dtype=None)
249 if sample_weight is not None:
C:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py in check_array(array, accept_sparse, dtype, order, copy, force_all_finite, ensure_2d, allow_nd, ensure_min_samples, ensure_min_features, warn_on_dtype, estimator)
431 force_all_finite)
432 else:
--> 433 array = np.array(array, dtype=dtype, order=order, copy=copy)
434
435 if ensure_2d:
ValueError: could not convert string to float: 'never'
This dataset contains a mix of continuous and categorical variables.
In [15]:
cols = ['enrollee_id', 'city', 'city_development_index', 'gender',
'relevent_experience', 'enrolled_university', 'enrolled_university_degree',
'major_discipline', 'experience', 'company_size', 'company_type',
'last_new_job', 'training_hours', 'target']
df_raw.columns = cols
df_test.columns = cols[:-1]
In [18]:
train_cats(X_train_od);
apply_cats(X_test_od, X_train_od);
D:\Github\fastai\courses\ml1\fastai\structured.py:204: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
df[n] = pd.Categorical(c, categories=trn[n].cat.categories, ordered=True)
In [19]:
X_train_od.enrolled_university.cat.categories;
X_train_od.enrolled_university.cat.set_categories(['no_enrollment', 'Part time course', 'Full time course' ],\
ordered=True, inplace=True)
X_train_od.enrolled_university = X_train_od.enrolled_university.cat.codes
X_train_od.enrolled_university_degree.cat.categories;
X_train_od.enrolled_university_degree.cat.set_categories(['Primary School','High School','Graduate', 'Masters', 'Phd',],\
ordered=True, inplace=True)
X_train_od.enrolled_university_degree = X_train_od.enrolled_university_degree.cat.codes
X_train_od.relevent_experience.cat.set_categories(['No relevent experience','Has relevent experience'],\
ordered=True, inplace=True)
X_train_od.relevent_experience = X_train_od.relevent_experience.cat.codes
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\generic.py:3110: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
self[name] = value
In [20]:
X_test_od.enrolled_university.cat.categories;
X_test_od.enrolled_university.cat.set_categories(['no_enrollment', 'Part time course', 'Full time course' ],\
ordered=True, inplace=True)
X_test_od.enrolled_university = X_test_od.enrolled_university.cat.codes
X_test_od.enrolled_university_degree.cat.categories;
X_test_od.enrolled_university_degree.cat.set_categories(['Primary School','High School','Graduate', 'Masters', 'Phd',],\
ordered=True, inplace=True)
X_test_od.enrolled_university_degree = X_test_od.enrolled_university_degree.cat.codes
X_test_od.relevent_experience.cat.set_categories(['No relevent experience','Has relevent experience'],\
ordered=True, inplace=True)
X_test_od.relevent_experience = X_test_od.relevent_experience.cat.codes
C:\ProgramData\Anaconda3\lib\site-packages\pandas\core\generic.py:3110: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
self[name] = value
In [16]:
drop = ['enrollee_id']
df_raw.drop(drop, axis=1,inplace=True)
df_test.drop(drop, axis=1,inplace=True)
In [17]:
df_raw['enrolled_university_degree'].fillna(df_raw['enrolled_university_degree'].mode()[0],inplace=True)
df_raw['enrolled_university'].fillna(df_raw['enrolled_university'].mode()[0],inplace=True)
df_test['enrolled_university_degree'].fillna(df_test['enrolled_university_degree'].mode()[0],inplace=True)
df_test['enrolled_university'].fillna(df_test['enrolled_university'].mode()[0],inplace=True)
In [114]:
df, y, nas, = proc_df(df_raw, 'target', max_n_cat=20,)
In [66]:
from sklearn.model_selection import train_test_split
X_train, X_valid, y_train, y_valid = train_test_split(df, y, test_size=0.2, random_state=42, stratify = y)
def split_vals(a,n): return a[:n].copy(), a[n:].copy()
n_valid = 2000 # same as Kaggle's test set size
n_trn = len(df)-n_valid
raw_train, raw_valid = split_vals(df_raw, n_trn)
X_train, X_valid = split_vals(df, n_trn)
y_train, y_valid = split_vals(y, n_trn)
X_train.shape, y_train.shape, X_valid.shape
Out[66]:
((16359, 41), (16359,), (2000, 41))
In [70]:
def logloss(x,y): return metrics.log_loss(y_true = y, y_pred = x)
def print_score(m):
print('Train Loss, Valid Loss, R**2 Train, R**2 Valid, OOB_Score(optional)')
res = [logloss(m.predict_proba(X_train), y_train), logloss(m.predict_proba(X_valid), y_valid),
m.score(X_train, y_train), m.score(X_valid, y_valid)]
if hasattr(m, 'oob_score_'): res.append(m.oob_score_)
print(res)
In [68]:
m = RandomForestClassifier(n_estimators=20,n_jobs=-1, max_depth=5, max_features='auto')
m.fit(X_train, y_train)
print_score(m)
Train Loss, Valid Loss, R**2 Train, R**2 Valid, OOB_Score(optional)
[0.36985482373263973, 0.36430670428351336, 0.86710679136866553, 0.87450000000000006]
In [77]:
draw_tree(m.estimators_[0], df, precision=3)
In [73]:
m = RandomForestClassifier(n_estimators=10, n_jobs=-1, oob_score=True, max_depth=5)
m.fit(X_train, y_train)
print_score(m)
C:\ProgramData\Anaconda3\lib\site-packages\sklearn\ensemble\forest.py:453: UserWarning: Some inputs do not have OOB scores. This probably means too few trees were used to compute any reliable oob estimates.
warn("Some inputs do not have OOB scores. "
C:\ProgramData\Anaconda3\lib\site-packages\sklearn\ensemble\forest.py:458: RuntimeWarning: invalid value encountered in true_divide
predictions[k].sum(axis=1)[:, np.newaxis])
Train Loss, Valid Loss, R**2 Train, R**2 Valid, OOB_Score(optional)
[0.36979450404333986, 0.36537382401608476, 0.86710679136866553, 0.87450000000000006, 0.86692340607616603]
In [74]:
m = RandomForestClassifier(n_estimators=200, min_samples_leaf=3,max_features=0.5, n_jobs=-1, oob_score=True)
m.fit(X_train, y_train)
print_score(m)
Train Loss, Valid Loss, R**2 Train, R**2 Valid, OOB_Score(optional)
[0.20387255010799227, 0.38711766787524177, 0.89974937343358397, 0.87350000000000005, 0.86484503942783786]
In [75]:
fi = rf_feat_importance(m, df); fi[:10]
Out[75]:
cols
imp
6
training_hours
0.257144
5
experience
0.149266
1
city_development_index
0.118949
0
city
0.094909
4
enrolled_university_degree
0.038956
3
enrolled_university
0.031631
34
last_new_job_1
0.025014
8
gender_Male
0.019788
2
relevent_experience
0.019407
10
gender_nan
0.017197
In [76]:
fi.plot('cols', 'imp', figsize=(10,6), legend=False);
In [77]:
def plot_fi(fi): return fi.plot('cols', 'imp', 'barh', figsize=(12,7), legend=False)
In [78]:
plot_fi(fi[:30]);
In [85]:
to_keep = fi[fi.imp>0.002].cols; len(to_keep)
Out[85]:
42
In [87]:
df_keep = df[to_keep].copy()
X_train, X_valid = split_vals(df_keep, n_trn)
In [97]:
m = RandomForestRegressor(n_estimators=200, max_features=0.5,
n_jobs=-1, oob_score=True)
m.fit(X_train, y_train)
print_score(m)
Train Loss, Valid Loss, R**2 Train, R**2 Valid
[0.094103076588840262, 0.38694119197589372, 0.86124718844888137, -0.026665415171825746, -0.013963884820979544]
In [91]:
fi = rf_feat_importance(m, df_keep)
plot_fi(fi[:25]);
In [92]:
from scipy.cluster import hierarchy as hc
In [93]:
corr = np.round(scipy.stats.spearmanr(df_keep).correlation, 4)
corr_condensed = hc.distance.squareform(1-corr)
z = hc.linkage(corr_condensed, method='average')
fig = plt.figure(figsize=(16,10))
dendrogram = hc.dendrogram(z, labels=df_keep.columns, orientation='left', leaf_font_size=16)
plt.show()
In [94]:
def get_oob(df):
m = RandomForestRegressor(n_estimators=200, max_features=0.6, n_jobs=-1, oob_score=True)
x, _ = split_vals(df, n_trn)
m.fit(x, y_train)
return m.oob_score_
In [79]:
m
Out[79]:
RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',
max_depth=None, max_features=0.5, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=3, min_samples_split=2,
min_weight_fraction_leaf=0.0, n_estimators=200, n_jobs=-1,
oob_score=True, random_state=None, verbose=0, warm_start=False)
In [118]:
m = RandomForestClassifier(n_estimators=200, min_samples_leaf=3,max_features=0.5, n_jobs=-1, oob_score=True)
m.fit(df, y)
print_score(m)
Train Loss, Valid Loss, R**2 Train, R**2 Valid, OOB_Score(optional)
[0.20420249978426797, 0.2008521456131836, 0.89730423620025679, 0.89949999999999997, 0.86507979737458462]
In [119]:
df_test['target'] = y[:df_test.shape[0]]
df_test_, _, _ = proc_df(df_test, 'target', na_dict=nas, max_n_cat=20)
In [120]:
set(df.columns) - set(df_test_.columns)
Out[120]:
set()
In [121]:
set(df_test_.columns) - set(df.columns)
Out[121]:
set()
In [122]:
preds = m.predict_proba(df_test_)
In [49]:
def make_submission(probs):
sample = pd.read_csv(f'{PATH}\\AV_Stud_2\\sample_submission.csv')
submit = sample.copy()
submit['target'] = probs
return submit
In [112]:
submit = make_submission(preds)
submit.to_csv(f'{PATH}\\AV_Stud_2\\rf.csv', index=False)
submit.head(2)
Out[112]:
enrollee_id
target
0
16548
0.815661
1
12036
0.027220
In [17]:
#drop id if original data is imported
target = df_raw.target.values
df_raw.drop(['target'],axis=1, inplace=True)
#df_test.drop('id', axis=1, inplace=True)
features = df_raw.columns
numeric_features = []
categorical_features = []
i = 0
index = []
for dtype, feature in zip(df_raw.dtypes, df_raw.columns):
if dtype == object:
#print(column)
#print(train_data[column].describe())
categorical_features.append(feature)
index.append(i)
else:
numeric_features.append(feature)
i +=1
categorical_features;
train_cats(df_raw);
apply_cats(df_test, df_raw)
X_train_num = df_raw.drop(categorical_features,axis=1) #numeric ones
X_test_num = df_test.drop(categorical_features,axis=1) #numeric ones
X_train_od = df_raw[categorical_features] #numeric ones
X_test_od = df_test[categorical_features] #numeric ones
In [69]:
import category_encoders as cat_ed
In [70]:
encoder = cat_ed.backward_difference.BackwardDifferenceEncoder(drop_invariant=True,cols=categorical_features)
df_raw = encoder.fit_transform(df_raw, verbose=1)
df_test = encoder.transform(df_test)
In [71]:
df_raw.shape, df_test.shape
Out[71]:
((18359, 183), (15021, 183))
In [51]:
def Intersection(lst1, lst2):
return list(set(lst1).intersection(lst2))
In [70]:
model=CatBoostClassifier(iterations=1020, depth=8, learning_rate=0.06, loss_function= 'Logloss')
model.fit(X_stack_train, target)
0: learn: 0.6503847 total: 282ms remaining: 4m 47s
1: learn: 0.6129987 total: 351ms remaining: 2m 58s
2: learn: 0.5796037 total: 421ms remaining: 2m 22s
3: learn: 0.5514890 total: 485ms remaining: 2m 3s
4: learn: 0.5270214 total: 552ms remaining: 1m 52s
5: learn: 0.5064879 total: 618ms remaining: 1m 44s
6: learn: 0.4889237 total: 685ms remaining: 1m 39s
7: learn: 0.4731387 total: 749ms remaining: 1m 34s
8: learn: 0.4591367 total: 825ms remaining: 1m 32s
9: learn: 0.4473548 total: 894ms remaining: 1m 30s
10: learn: 0.4366933 total: 961ms remaining: 1m 28s
11: learn: 0.4274822 total: 1.03s remaining: 1m 26s
12: learn: 0.4196324 total: 1.09s remaining: 1m 24s
13: learn: 0.4130140 total: 1.15s remaining: 1m 22s
14: learn: 0.4067396 total: 1.22s remaining: 1m 21s
15: learn: 0.4013903 total: 1.28s remaining: 1m 20s
16: learn: 0.3965975 total: 1.35s remaining: 1m 19s
17: learn: 0.3923884 total: 1.41s remaining: 1m 18s
18: learn: 0.3893522 total: 1.48s remaining: 1m 17s
19: learn: 0.3860844 total: 1.54s remaining: 1m 17s
20: learn: 0.3832146 total: 1.61s remaining: 1m 16s
21: learn: 0.3806680 total: 1.68s remaining: 1m 16s
22: learn: 0.3786167 total: 1.75s remaining: 1m 15s
23: learn: 0.3764654 total: 1.82s remaining: 1m 15s
24: learn: 0.3746455 total: 1.88s remaining: 1m 15s
25: learn: 0.3728226 total: 1.96s remaining: 1m 14s
26: learn: 0.3712116 total: 2.02s remaining: 1m 14s
27: learn: 0.3700237 total: 2.08s remaining: 1m 13s
28: learn: 0.3689403 total: 2.15s remaining: 1m 13s
29: learn: 0.3676505 total: 2.21s remaining: 1m 13s
30: learn: 0.3663333 total: 2.28s remaining: 1m 12s
31: learn: 0.3655494 total: 2.34s remaining: 1m 12s
32: learn: 0.3646756 total: 2.41s remaining: 1m 12s
33: learn: 0.3636094 total: 2.47s remaining: 1m 11s
34: learn: 0.3624883 total: 2.54s remaining: 1m 11s
35: learn: 0.3616918 total: 2.6s remaining: 1m 11s
36: learn: 0.3610149 total: 2.66s remaining: 1m 10s
37: learn: 0.3601671 total: 2.73s remaining: 1m 10s
38: learn: 0.3597110 total: 2.79s remaining: 1m 10s
39: learn: 0.3591137 total: 2.86s remaining: 1m 10s
40: learn: 0.3585053 total: 2.93s remaining: 1m 9s
41: learn: 0.3578670 total: 3s remaining: 1m 9s
42: learn: 0.3571983 total: 3.07s remaining: 1m 9s
43: learn: 0.3564365 total: 3.14s remaining: 1m 9s
44: learn: 0.3558246 total: 3.21s remaining: 1m 9s
45: learn: 0.3552913 total: 3.28s remaining: 1m 9s
46: learn: 0.3549967 total: 3.34s remaining: 1m 9s
47: learn: 0.3544724 total: 3.41s remaining: 1m 9s
48: learn: 0.3536402 total: 3.48s remaining: 1m 8s
49: learn: 0.3533190 total: 3.54s remaining: 1m 8s
50: learn: 0.3527587 total: 3.61s remaining: 1m 8s
51: learn: 0.3522457 total: 3.68s remaining: 1m 8s
52: learn: 0.3517290 total: 3.74s remaining: 1m 8s
53: learn: 0.3511570 total: 3.81s remaining: 1m 8s
54: learn: 0.3507324 total: 3.88s remaining: 1m 8s
55: learn: 0.3502414 total: 3.95s remaining: 1m 7s
56: learn: 0.3498702 total: 4.01s remaining: 1m 7s
57: learn: 0.3495709 total: 4.08s remaining: 1m 7s
58: learn: 0.3490289 total: 4.15s remaining: 1m 7s
59: learn: 0.3488547 total: 4.22s remaining: 1m 7s
60: learn: 0.3485157 total: 4.29s remaining: 1m 7s
61: learn: 0.3481995 total: 4.36s remaining: 1m 7s
62: learn: 0.3477509 total: 4.43s remaining: 1m 7s
63: learn: 0.3473437 total: 4.5s remaining: 1m 7s
64: learn: 0.3471004 total: 4.57s remaining: 1m 7s
65: learn: 0.3465762 total: 4.63s remaining: 1m 6s
66: learn: 0.3463527 total: 4.7s remaining: 1m 6s
67: learn: 0.3460447 total: 4.76s remaining: 1m 6s
68: learn: 0.3456890 total: 4.83s remaining: 1m 6s
69: learn: 0.3455672 total: 4.89s remaining: 1m 6s
70: learn: 0.3451506 total: 4.95s remaining: 1m 6s
71: learn: 0.3448752 total: 5.02s remaining: 1m 6s
72: learn: 0.3445263 total: 5.08s remaining: 1m 5s
73: learn: 0.3441255 total: 5.15s remaining: 1m 5s
74: learn: 0.3437229 total: 5.22s remaining: 1m 5s
75: learn: 0.3435462 total: 5.28s remaining: 1m 5s
76: learn: 0.3432950 total: 5.34s remaining: 1m 5s
77: learn: 0.3429279 total: 5.41s remaining: 1m 5s
78: learn: 0.3426763 total: 5.47s remaining: 1m 5s
79: learn: 0.3423088 total: 5.54s remaining: 1m 5s
80: learn: 0.3420792 total: 5.6s remaining: 1m 4s
81: learn: 0.3415920 total: 5.67s remaining: 1m 4s
82: learn: 0.3410071 total: 5.74s remaining: 1m 4s
83: learn: 0.3407647 total: 5.81s remaining: 1m 4s
---------------------------------------------------------------------------
KeyboardInterrupt Traceback (most recent call last)
<ipython-input-70-3f6458ffdb95> in <module>()
1 model=CatBoostClassifier(iterations=1020, depth=8, learning_rate=0.06, loss_function= 'Logloss')
----> 2 model.fit(X_stack_train, target)
C:\ProgramData\Anaconda3\lib\site-packages\catboost\core.py in fit(self, X, y, cat_features, sample_weight, baseline, use_best_model, eval_set, verbose, logging_level, plot)
1298 model : CatBoost
1299 """
-> 1300 self._fit(X, y, cat_features, None, sample_weight, None, None, baseline, use_best_model, eval_set, verbose, logging_level, plot)
1301 if y is not None:
1302 setattr(self, "_classes", np.unique(y))
C:\ProgramData\Anaconda3\lib\site-packages\catboost\core.py in _fit(self, X, y, cat_features, pairs, sample_weight, query_id, pairs_weight, baseline, use_best_model, eval_set, verbose, logging_level, plot)
571 raise ImportError(str(e))
572 with log_fixup():
--> 573 self._train(X, eval_set, params)
574 if calc_feature_importance:
575 setattr(self, "_feature_importance", self.get_feature_importance(X))
_catboost.pyx in _catboost._CatBoostBase._train()
_catboost.pyx in _catboost._CatBoost._train()
_catboost.pyx in _catboost._CatBoost._train()
KeyboardInterrupt:
In [89]:
preds = model.predict_proba(df_test)[:,1]
In [91]:
m = RandomForestClassifier(n_estimators=200,n_jobs=-1, max_features='auto')
m.fit(df_raw, target)
Out[91]:
RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',
max_depth=None, max_features='auto', max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=2,
min_weight_fraction_leaf=0.0, n_estimators=200, n_jobs=-1,
oob_score=False, random_state=None, verbose=0,
warm_start=False)
In [92]:
fi = rf_feat_importance(m, df_raw); fi[:10]
Out[92]:
cols
imp
182
col_training_hours
0.216338
181
col_city_development_index
0.051304
121
col_gender_1
0.030305
129
col_enrolled_university_degree_2
0.027899
176
col_last_new_job_2
0.026573
124
col_relevent_experience_1
0.023331
126
col_enrolled_university_2
0.023020
177
col_last_new_job_3
0.018803
178
col_last_new_job_4
0.017770
169
col_company_type_1
0.015755
In [97]:
preds = m.predict_proba(df_test)[:,1]
In [108]:
X_train['target'] = target
In [106]:
X_train['city_development_index'].value_counts().sort_values(ascending=False).head(20)
Out[106]:
0.920 5185
0.624 1672
0.910 1654
0.926 1472
0.698 655
0.897 624
0.939 544
0.855 455
0.924 318
0.804 313
0.884 281
0.887 271
0.754 264
0.913 217
0.899 194
0.802 188
0.925 178
0.893 175
0.878 156
0.743 152
Name: city_development_index, dtype: int64
In [113]:
X_train.columns
Out[113]:
Index(['enrollee_id', 'city_development_index', 'training_hours', 'target'], dtype='object')
In [116]:
with sns.axes_style("white"):
sns.jointplot(x='training_hours', y='city_development_index',data=X_train, kind="hex", color='k');
In [142]:
sns.lmplot('training_hours','city_development_index', X_train, 'target', x_bins= 50)
Out[142]:
<seaborn.axisgrid.FacetGrid at 0x2be282f8550>
In [147]:
X_test.columns, X_train.columns
Out[147]:
(Index(['city_development_index', 'training_hours'], dtype='object'),
Index(['city_development_index', 'training_hours', 'target'], dtype='object'))
In [155]:
preds = X_test.training_hours.map(X_train.groupby('training_hours')['target'].mean())
In [156]:
preds
Out[156]:
0 0.101852
1 0.120690
2 0.118367
3 0.115385
4 0.118421
5 0.150000
6 0.147982
7 0.081818
8 0.075758
9 0.142857
10 0.123404
11 0.107345
12 0.206897
13 0.177778
14 0.120833
15 0.166667
16 0.129825
17 0.138996
18 0.118143
19 0.123404
20 0.119048
21 0.131868
22 0.103093
23 0.113043
24 0.000000
25 0.092896
26 0.076923
27 0.117318
28 0.159091
29 0.109091
...
14991 0.108108
14992 0.166667
14993 0.149194
14994 0.428571
14995 0.120833
14996 0.139665
14997 0.160494
14998 0.153846
14999 0.104348
15000 0.131579
15001 0.131868
15002 0.125000
15003 0.152344
15004 0.171429
15005 0.092593
15006 0.169231
15007 0.134831
15008 0.129825
15009 0.123404
15010 0.088889
15011 0.155340
15012 0.081818
15013 0.095238
15014 0.152344
15015 0.103093
15016 0.171429
15017 0.000000
15018 0.180000
15019 0.104762
15020 0.069307
Name: training_hours, Length: 15021, dtype: float64
In [57]:
X_train_od['y'] = target
# plt.figure(figsize=(30,32))
for i in range(len(categorical_features)):
plt.figure(figsize=(10,10))
c = categorical_features[i]
means = X_train_od.groupby(c).y.mean()
stds = X_train_od.groupby(c).y.std().fillna(0)
maxs = X_train_od.groupby(c).y.max()
mins = X_train_od.groupby(c).y.min()
ddd = pd.concat([means, stds, maxs, mins], axis=1);
ddd.columns = ['means', 'stds', 'maxs', 'mins']
ddd.sort_values('means', inplace=True)
ax = sns.countplot(x=c, order=ddd.index.values,data=X_train_od, hue='y')
plt.title(c)
for p in ax.patches:
x=p.get_bbox().get_points()[:,0]
y=p.get_bbox().get_points()[1,1]
ax.annotate('{:.0f}'.format(y), (x.mean(), y), ha='center', va='bottom')
C:\ProgramData\Anaconda3\lib\site-packages\ipykernel_launcher.py:1: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
"""Entry point for launching an IPython kernel.
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
C:\ProgramData\Anaconda3\lib\site-packages\IPython\core\formatters.py in __call__(self, obj)
330 pass
331 else:
--> 332 return printer(obj)
333 # Finally look for special method names
334 method = get_real_method(obj, self.print_method)
C:\ProgramData\Anaconda3\lib\site-packages\IPython\core\pylabtools.py in <lambda>(fig)
235
236 if 'png' in formats:
--> 237 png_formatter.for_type(Figure, lambda fig: print_figure(fig, 'png', **kwargs))
238 if 'retina' in formats or 'png2x' in formats:
239 png_formatter.for_type(Figure, lambda fig: retina_figure(fig, **kwargs))
C:\ProgramData\Anaconda3\lib\site-packages\IPython\core\pylabtools.py in print_figure(fig, fmt, bbox_inches, **kwargs)
119
120 bytes_io = BytesIO()
--> 121 fig.canvas.print_figure(bytes_io, **kw)
122 data = bytes_io.getvalue()
123 if fmt == 'svg':
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\backend_bases.py in print_figure(self, filename, dpi, facecolor, edgecolor, orientation, format, **kwargs)
2257 orientation=orientation,
2258 bbox_inches_restore=_bbox_inches_restore,
-> 2259 **kwargs)
2260 finally:
2261 if bbox_inches and restore_bbox:
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\backends\backend_agg.py in print_png(self, filename_or_obj, *args, **kwargs)
505
506 def print_png(self, filename_or_obj, *args, **kwargs):
--> 507 FigureCanvasAgg.draw(self)
508 renderer = self.get_renderer()
509 original_dpi = renderer.dpi
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\backends\backend_agg.py in draw(self)
428 if toolbar:
429 toolbar.set_cursor(cursors.WAIT)
--> 430 self.figure.draw(self.renderer)
431 finally:
432 if toolbar:
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
53 renderer.start_filter()
54
---> 55 return draw(artist, renderer, *args, **kwargs)
56 finally:
57 if artist.get_agg_filter() is not None:
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\figure.py in draw(self, renderer)
1293
1294 mimage._draw_list_compositing_images(
-> 1295 renderer, self, artists, self.suppressComposite)
1296
1297 renderer.close_group('figure')
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\image.py in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
136 if not_composite or not has_images:
137 for a in artists:
--> 138 a.draw(renderer)
139 else:
140 # Composite any adjacent images together
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
53 renderer.start_filter()
54
---> 55 return draw(artist, renderer, *args, **kwargs)
56 finally:
57 if artist.get_agg_filter() is not None:
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axes\_base.py in draw(self, renderer, inframe)
2397 renderer.stop_rasterizing()
2398
-> 2399 mimage._draw_list_compositing_images(renderer, self, artists)
2400
2401 renderer.close_group('axes')
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\image.py in _draw_list_compositing_images(renderer, parent, artists, suppress_composite)
136 if not_composite or not has_images:
137 for a in artists:
--> 138 a.draw(renderer)
139 else:
140 # Composite any adjacent images together
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
53 renderer.start_filter()
54
---> 55 return draw(artist, renderer, *args, **kwargs)
56 finally:
57 if artist.get_agg_filter() is not None:
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\axis.py in draw(self, renderer, *args, **kwargs)
1145 self._update_label_position(ticklabelBoxes, ticklabelBoxes2)
1146
-> 1147 self.label.draw(renderer)
1148
1149 self._update_offset_text_position(ticklabelBoxes, ticklabelBoxes2)
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\artist.py in draw_wrapper(artist, renderer, *args, **kwargs)
53 renderer.start_filter()
54
---> 55 return draw(artist, renderer, *args, **kwargs)
56 finally:
57 if artist.get_agg_filter() is not None:
C:\ProgramData\Anaconda3\lib\site-packages\matplotlib\text.py in draw(self, renderer)
761 posy = float(textobj.convert_yunits(textobj._y))
762 if not np.isfinite(posx) or not np.isfinite(posy):
--> 763 raise ValueError("posx and posy should be finite values")
764 posx, posy = trans.transform_point((posx, posy))
765 canvasw, canvash = renderer.get_canvas_width_height()
ValueError: posx and posy should be finite values
<matplotlib.figure.Figure at 0x2478a3a6438>
In [64]:
# This way we have randomness and are able to reproduce the behaviour within this cell.
np.random.seed(13)
def impact_coding(data, feature, target='y'):
'''
In this implementation we get the values and the dictionary as two different steps.
This is just because initially we were ignoring the dictionary as a result variable.
In this implementation the KFolds use shuffling. If you want reproducibility the cv
could be moved to a parameter.
'''
n_folds = 7
n_inner_folds = 5
impact_coded = pd.Series()
oof_default_mean = data[target].mean() # Gobal mean to use by default (you could further tune this)
kf = KFold(n_splits=n_folds, shuffle=True)
oof_mean_cv = pd.DataFrame()
split = 0
for infold, oof in kf.split(data[feature]):
impact_coded_cv = pd.Series()
kf_inner = KFold(n_splits=n_inner_folds, shuffle=True)
inner_split = 0
inner_oof_mean_cv = pd.DataFrame()
oof_default_inner_mean = data.iloc[infold][target].mean()
for infold_inner, oof_inner in kf_inner.split(data.iloc[infold]):
# The mean to apply to the inner oof split (a 1/n_folds % based on the rest)
oof_mean = data.iloc[infold_inner].groupby(by=feature)[target].mean()
impact_coded_cv = impact_coded_cv.append(data.iloc[infold].apply(
lambda x: oof_mean[x[feature]]
if x[feature] in oof_mean.index
else oof_default_inner_mean
, axis=1))
# Also populate mapping (this has all group -> mean for all inner CV folds)
inner_oof_mean_cv = inner_oof_mean_cv.join(pd.DataFrame(oof_mean), rsuffix=inner_split, how='outer')
inner_oof_mean_cv.fillna(value=oof_default_inner_mean, inplace=True)
inner_split += 1
# Also populate mapping
oof_mean_cv = oof_mean_cv.join(pd.DataFrame(inner_oof_mean_cv), rsuffix=split, how='outer')
oof_mean_cv.fillna(value=oof_default_mean, inplace=True)
split += 1
impact_coded = impact_coded.append(data.iloc[oof].apply(
lambda x: inner_oof_mean_cv.loc[x[feature]].mean()
if x[feature] in inner_oof_mean_cv.index
else oof_default_mean
, axis=1))
return impact_coded, oof_mean_cv.mean(axis=1), oof_default_mean
# Apply the encoding to training and test data, and preserve the mapping
X_train_od['y'] = target
impact_coding_map = {}
for f in categorical_features:
print("Impact coding for {}".format(f))
X_train_od["impact_encoded_{}".format(f)], impact_coding_mapping, default_coding = impact_coding(X_train_od, f)
impact_coding_map[f] = (impact_coding_mapping, default_coding)
mapping, default_mean = impact_coding_map[f]
X_test_od["impact_encoded_{}".format(f)] = X_test_od.apply(lambda x: mapping[x[f]]
if x[f] in mapping
else default_mean
, axis=1)
C:\ProgramData\Anaconda3\lib\site-packages\ipykernel_launcher.py:55: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
Impact coding for city
C:\ProgramData\Anaconda3\lib\site-packages\ipykernel_launcher.py:65: SettingWithCopyWarning:
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy
Impact coding for gender
Impact coding for relevent_experience
Impact coding for enrolled_university
Impact coding for enrolled_university_degree
Impact coding for major_discipline
Impact coding for experience
Impact coding for company_size
Impact coding for company_type
Impact coding for last_new_job
In [67]:
X_train_od.drop(categorical_features, axis=1, inplace=True)
X_test_od.drop(categorical_features, axis=1, inplace=True)
X_train_od.drop('y', axis=1, inplace=True)
In [104]:
X_stack_train, X_stack_test = np.hstack((X_train_num, X_train_od)), np.hstack((X_test_num, X_test_od))
In [105]:
model=CatBoostClassifier(iterations=1024, depth=8, learning_rate=0.06, loss_function= 'Logloss')
model.fit(X_stack_train, target)
0: learn: 0.6487793 total: 70.1ms remaining: 1m 11s
1: learn: 0.6110423 total: 141ms remaining: 1m 12s
2: learn: 0.5787638 total: 210ms remaining: 1m 11s
3: learn: 0.5510888 total: 282ms remaining: 1m 11s
4: learn: 0.5272061 total: 333ms remaining: 1m 7s
5: learn: 0.5057416 total: 404ms remaining: 1m 8s
6: learn: 0.4886206 total: 474ms remaining: 1m 8s
7: learn: 0.4717282 total: 555ms remaining: 1m 10s
8: learn: 0.4589159 total: 614ms remaining: 1m 9s
9: learn: 0.4468200 total: 686ms remaining: 1m 9s
10: learn: 0.4364113 total: 754ms remaining: 1m 9s
11: learn: 0.4280056 total: 936ms remaining: 1m 18s
12: learn: 0.4197143 total: 1.01s remaining: 1m 18s
13: learn: 0.4122720 total: 1.08s remaining: 1m 18s
14: learn: 0.4065293 total: 1.16s remaining: 1m 17s
15: learn: 0.4017786 total: 1.23s remaining: 1m 17s
16: learn: 0.3975269 total: 1.3s remaining: 1m 16s
17: learn: 0.3932339 total: 1.37s remaining: 1m 16s
18: learn: 0.3895112 total: 1.45s remaining: 1m 16s
19: learn: 0.3861101 total: 1.54s remaining: 1m 17s
20: learn: 0.3833600 total: 1.61s remaining: 1m 16s
21: learn: 0.3808690 total: 1.68s remaining: 1m 16s
22: learn: 0.3784602 total: 1.75s remaining: 1m 16s
23: learn: 0.3766088 total: 1.82s remaining: 1m 15s
24: learn: 0.3748081 total: 1.89s remaining: 1m 15s
25: learn: 0.3730617 total: 1.97s remaining: 1m 15s
26: learn: 0.3713147 total: 2.04s remaining: 1m 15s
27: learn: 0.3699120 total: 2.11s remaining: 1m 15s
28: learn: 0.3687353 total: 2.19s remaining: 1m 15s
29: learn: 0.3676694 total: 2.25s remaining: 1m 14s
30: learn: 0.3662559 total: 2.33s remaining: 1m 14s
31: learn: 0.3654474 total: 2.4s remaining: 1m 14s
32: learn: 0.3645364 total: 2.47s remaining: 1m 14s
33: learn: 0.3637165 total: 2.55s remaining: 1m 14s
34: learn: 0.3625755 total: 2.63s remaining: 1m 14s
35: learn: 0.3616069 total: 2.7s remaining: 1m 14s
36: learn: 0.3609096 total: 2.77s remaining: 1m 13s
37: learn: 0.3601893 total: 2.84s remaining: 1m 13s
38: learn: 0.3593454 total: 2.92s remaining: 1m 13s
39: learn: 0.3587070 total: 3s remaining: 1m 13s
40: learn: 0.3581563 total: 3.07s remaining: 1m 13s
41: learn: 0.3576101 total: 3.13s remaining: 1m 13s
42: learn: 0.3572270 total: 3.2s remaining: 1m 12s
43: learn: 0.3566449 total: 3.27s remaining: 1m 12s
44: learn: 0.3561598 total: 3.34s remaining: 1m 12s
45: learn: 0.3551549 total: 3.41s remaining: 1m 12s
46: learn: 0.3544258 total: 3.48s remaining: 1m 12s
47: learn: 0.3540021 total: 3.55s remaining: 1m 12s
48: learn: 0.3535017 total: 3.63s remaining: 1m 12s
49: learn: 0.3532651 total: 3.72s remaining: 1m 12s
50: learn: 0.3529212 total: 3.8s remaining: 1m 12s
51: learn: 0.3525292 total: 3.88s remaining: 1m 12s
52: learn: 0.3522614 total: 3.96s remaining: 1m 12s
53: learn: 0.3519793 total: 4.03s remaining: 1m 12s
54: learn: 0.3517468 total: 4.11s remaining: 1m 12s
55: learn: 0.3510718 total: 4.19s remaining: 1m 12s
56: learn: 0.3507290 total: 4.26s remaining: 1m 12s
57: learn: 0.3504284 total: 4.33s remaining: 1m 12s
58: learn: 0.3497545 total: 4.42s remaining: 1m 12s
59: learn: 0.3494694 total: 4.5s remaining: 1m 12s
60: learn: 0.3491505 total: 4.58s remaining: 1m 12s
61: learn: 0.3485977 total: 4.65s remaining: 1m 12s
62: learn: 0.3481857 total: 4.72s remaining: 1m 12s
63: learn: 0.3475708 total: 4.8s remaining: 1m 11s
64: learn: 0.3472300 total: 4.87s remaining: 1m 11s
65: learn: 0.3470052 total: 4.93s remaining: 1m 11s
66: learn: 0.3463661 total: 5.01s remaining: 1m 11s
67: learn: 0.3460976 total: 5.07s remaining: 1m 11s
68: learn: 0.3457943 total: 5.14s remaining: 1m 11s
69: learn: 0.3455970 total: 5.22s remaining: 1m 11s
70: learn: 0.3450362 total: 5.31s remaining: 1m 11s
71: learn: 0.3445144 total: 5.38s remaining: 1m 11s
72: learn: 0.3441411 total: 5.46s remaining: 1m 11s
73: learn: 0.3438303 total: 5.53s remaining: 1m 10s
74: learn: 0.3434533 total: 5.59s remaining: 1m 10s
75: learn: 0.3432701 total: 5.66s remaining: 1m 10s
76: learn: 0.3430851 total: 5.73s remaining: 1m 10s
77: learn: 0.3428044 total: 5.79s remaining: 1m 10s
78: learn: 0.3424727 total: 5.87s remaining: 1m 10s
79: learn: 0.3423256 total: 5.93s remaining: 1m 10s
80: learn: 0.3418833 total: 6s remaining: 1m 9s
81: learn: 0.3414547 total: 6.07s remaining: 1m 9s
82: learn: 0.3411234 total: 6.14s remaining: 1m 9s
83: learn: 0.3407434 total: 6.22s remaining: 1m 9s
84: learn: 0.3405643 total: 6.29s remaining: 1m 9s
85: learn: 0.3402572 total: 6.36s remaining: 1m 9s
86: learn: 0.3400475 total: 6.43s remaining: 1m 9s
87: learn: 0.3397083 total: 6.49s remaining: 1m 9s
88: learn: 0.3395607 total: 6.56s remaining: 1m 8s
89: learn: 0.3392905 total: 6.63s remaining: 1m 8s
90: learn: 0.3387817 total: 6.71s remaining: 1m 8s
91: learn: 0.3385907 total: 6.79s remaining: 1m 8s
92: learn: 0.3384100 total: 6.86s remaining: 1m 8s
93: learn: 0.3380851 total: 6.94s remaining: 1m 8s
94: learn: 0.3377706 total: 7.01s remaining: 1m 8s
95: learn: 0.3374683 total: 7.08s remaining: 1m 8s
96: learn: 0.3372419 total: 7.16s remaining: 1m 8s
97: learn: 0.3368557 total: 7.23s remaining: 1m 8s
98: learn: 0.3365975 total: 7.3s remaining: 1m 8s
99: learn: 0.3362537 total: 7.38s remaining: 1m 8s
100: learn: 0.3360359 total: 7.46s remaining: 1m 8s
101: learn: 0.3355955 total: 7.54s remaining: 1m 8s
102: learn: 0.3352702 total: 7.63s remaining: 1m 8s
103: learn: 0.3350304 total: 7.71s remaining: 1m 8s
104: learn: 0.3346011 total: 7.79s remaining: 1m 8s
105: learn: 0.3344823 total: 7.86s remaining: 1m 8s
106: learn: 0.3342339 total: 7.93s remaining: 1m 7s
107: learn: 0.3338375 total: 8s remaining: 1m 7s
108: learn: 0.3335379 total: 8.08s remaining: 1m 7s
109: learn: 0.3332855 total: 8.17s remaining: 1m 7s
110: learn: 0.3330382 total: 8.25s remaining: 1m 7s
111: learn: 0.3326651 total: 8.33s remaining: 1m 7s
112: learn: 0.3325026 total: 8.4s remaining: 1m 7s
113: learn: 0.3321578 total: 8.47s remaining: 1m 7s
114: learn: 0.3317852 total: 8.54s remaining: 1m 7s
115: learn: 0.3316058 total: 8.59s remaining: 1m 7s
116: learn: 0.3313054 total: 8.66s remaining: 1m 7s
117: learn: 0.3311150 total: 8.72s remaining: 1m 6s
118: learn: 0.3308952 total: 8.79s remaining: 1m 6s
119: learn: 0.3307181 total: 8.85s remaining: 1m 6s
120: learn: 0.3304838 total: 8.92s remaining: 1m 6s
121: learn: 0.3301741 total: 8.99s remaining: 1m 6s
122: learn: 0.3299940 total: 9.06s remaining: 1m 6s
123: learn: 0.3296606 total: 9.12s remaining: 1m 6s
124: learn: 0.3294536 total: 9.18s remaining: 1m 6s
125: learn: 0.3290557 total: 9.24s remaining: 1m 5s
126: learn: 0.3287496 total: 9.3s remaining: 1m 5s
127: learn: 0.3284182 total: 9.36s remaining: 1m 5s
128: learn: 0.3280385 total: 9.42s remaining: 1m 5s
129: learn: 0.3277752 total: 9.49s remaining: 1m 5s
130: learn: 0.3275295 total: 9.55s remaining: 1m 5s
131: learn: 0.3272517 total: 9.61s remaining: 1m 4s
132: learn: 0.3271297 total: 9.67s remaining: 1m 4s
133: learn: 0.3269605 total: 9.73s remaining: 1m 4s
134: learn: 0.3266003 total: 9.81s remaining: 1m 4s
135: learn: 0.3263650 total: 9.89s remaining: 1m 4s
136: learn: 0.3261801 total: 9.97s remaining: 1m 4s
137: learn: 0.3259249 total: 10s remaining: 1m 4s
138: learn: 0.3256454 total: 10.1s remaining: 1m 4s
139: learn: 0.3254551 total: 10.2s remaining: 1m 4s
140: learn: 0.3253393 total: 10.2s remaining: 1m 3s
141: learn: 0.3250119 total: 10.3s remaining: 1m 3s
142: learn: 0.3247353 total: 10.3s remaining: 1m 3s
143: learn: 0.3245676 total: 10.4s remaining: 1m 3s
144: learn: 0.3243389 total: 10.5s remaining: 1m 3s
145: learn: 0.3241038 total: 10.5s remaining: 1m 3s
146: learn: 0.3238108 total: 10.6s remaining: 1m 3s
147: learn: 0.3236137 total: 10.7s remaining: 1m 3s
148: learn: 0.3233818 total: 10.8s remaining: 1m 3s
149: learn: 0.3232724 total: 10.9s remaining: 1m 3s
150: learn: 0.3231246 total: 10.9s remaining: 1m 3s
151: learn: 0.3229595 total: 11s remaining: 1m 3s
152: learn: 0.3225603 total: 11.1s remaining: 1m 3s
153: learn: 0.3221368 total: 11.1s remaining: 1m 2s
154: learn: 0.3219848 total: 11.2s remaining: 1m 3s
155: learn: 0.3217671 total: 11.3s remaining: 1m 3s
156: learn: 0.3213205 total: 11.4s remaining: 1m 2s
157: learn: 0.3211423 total: 11.5s remaining: 1m 2s
158: learn: 0.3208643 total: 11.5s remaining: 1m 2s
159: learn: 0.3205510 total: 11.6s remaining: 1m 2s
160: learn: 0.3203034 total: 11.6s remaining: 1m 2s
161: learn: 0.3199514 total: 11.7s remaining: 1m 2s
162: learn: 0.3197771 total: 11.8s remaining: 1m 2s
163: learn: 0.3196553 total: 11.8s remaining: 1m 2s
164: learn: 0.3194160 total: 11.9s remaining: 1m 1s
165: learn: 0.3191698 total: 11.9s remaining: 1m 1s
166: learn: 0.3188390 total: 12s remaining: 1m 1s
167: learn: 0.3185741 total: 12.1s remaining: 1m 1s
168: learn: 0.3181568 total: 12.2s remaining: 1m 1s
169: learn: 0.3178827 total: 12.2s remaining: 1m 1s
170: learn: 0.3176774 total: 12.3s remaining: 1m 1s
171: learn: 0.3175355 total: 12.4s remaining: 1m 1s
172: learn: 0.3175343 total: 12.4s remaining: 1m 1s
173: learn: 0.3172387 total: 12.5s remaining: 1m
174: learn: 0.3169713 total: 12.5s remaining: 1m
175: learn: 0.3167101 total: 12.6s remaining: 1m
176: learn: 0.3164490 total: 12.7s remaining: 1m
177: learn: 0.3161657 total: 12.7s remaining: 1m
178: learn: 0.3159494 total: 12.8s remaining: 1m
179: learn: 0.3156602 total: 12.9s remaining: 1m
180: learn: 0.3154818 total: 13s remaining: 1m
181: learn: 0.3152783 total: 13s remaining: 1m
182: learn: 0.3149554 total: 13.1s remaining: 1m
183: learn: 0.3147993 total: 13.2s remaining: 1m
184: learn: 0.3144221 total: 13.2s remaining: 60s
185: learn: 0.3141687 total: 13.3s remaining: 59.9s
186: learn: 0.3140601 total: 13.4s remaining: 59.8s
187: learn: 0.3139299 total: 13.4s remaining: 59.8s
188: learn: 0.3137911 total: 13.5s remaining: 59.7s
189: learn: 0.3136541 total: 13.6s remaining: 59.6s
190: learn: 0.3131839 total: 13.6s remaining: 59.5s
191: learn: 0.3129503 total: 13.7s remaining: 59.4s
192: learn: 0.3125430 total: 13.8s remaining: 59.3s
193: learn: 0.3123319 total: 13.8s remaining: 59.2s
194: learn: 0.3121716 total: 13.9s remaining: 59.1s
195: learn: 0.3118833 total: 14s remaining: 59s
196: learn: 0.3114904 total: 14s remaining: 58.9s
197: learn: 0.3113050 total: 14.1s remaining: 58.8s
198: learn: 0.3110528 total: 14.1s remaining: 58.6s
199: learn: 0.3107708 total: 14.2s remaining: 58.5s
200: learn: 0.3105728 total: 14.3s remaining: 58.4s
201: learn: 0.3101462 total: 14.3s remaining: 58.3s
202: learn: 0.3098639 total: 14.4s remaining: 58.2s
203: learn: 0.3095554 total: 14.5s remaining: 58.1s
204: learn: 0.3094279 total: 14.5s remaining: 58s
205: learn: 0.3092085 total: 14.6s remaining: 57.9s
206: learn: 0.3090676 total: 14.6s remaining: 57.8s
207: learn: 0.3088821 total: 14.7s remaining: 57.7s
208: learn: 0.3086838 total: 14.8s remaining: 57.6s
209: learn: 0.3085232 total: 14.8s remaining: 57.5s
210: learn: 0.3083173 total: 14.9s remaining: 57.4s
211: learn: 0.3080876 total: 15s remaining: 57.3s
212: learn: 0.3077803 total: 15s remaining: 57.2s
213: learn: 0.3074197 total: 15.1s remaining: 57.1s
214: learn: 0.3072465 total: 15.2s remaining: 57s
215: learn: 0.3071173 total: 15.2s remaining: 57s
216: learn: 0.3068748 total: 15.3s remaining: 56.9s
217: learn: 0.3066375 total: 15.4s remaining: 56.8s
218: learn: 0.3063991 total: 15.4s remaining: 56.7s
219: learn: 0.3061828 total: 15.5s remaining: 56.6s
220: learn: 0.3057734 total: 15.6s remaining: 56.6s
221: learn: 0.3054942 total: 15.6s remaining: 56.4s
222: learn: 0.3053042 total: 15.7s remaining: 56.3s
223: learn: 0.3050689 total: 15.8s remaining: 56.3s
224: learn: 0.3049754 total: 15.8s remaining: 56.1s
225: learn: 0.3047607 total: 15.9s remaining: 56s
226: learn: 0.3044763 total: 15.9s remaining: 55.9s
227: learn: 0.3042089 total: 16s remaining: 55.8s
228: learn: 0.3039639 total: 16.1s remaining: 55.8s
229: learn: 0.3036654 total: 16.1s remaining: 55.7s
230: learn: 0.3035583 total: 16.2s remaining: 55.6s
231: learn: 0.3033749 total: 16.3s remaining: 55.5s
232: learn: 0.3030653 total: 16.3s remaining: 55.4s
233: learn: 0.3027611 total: 16.4s remaining: 55.3s
234: learn: 0.3026476 total: 16.4s remaining: 55.2s
235: learn: 0.3025016 total: 16.5s remaining: 55.1s
236: learn: 0.3024566 total: 16.6s remaining: 55s
237: learn: 0.3022409 total: 16.6s remaining: 54.9s
238: learn: 0.3020341 total: 16.7s remaining: 54.8s
239: learn: 0.3018214 total: 16.8s remaining: 54.7s
240: learn: 0.3015730 total: 16.8s remaining: 54.6s
241: learn: 0.3012823 total: 16.9s remaining: 54.5s
242: learn: 0.3010097 total: 16.9s remaining: 54.5s
243: learn: 0.3007837 total: 17s remaining: 54.4s
244: learn: 0.3005628 total: 17.1s remaining: 54.3s
245: learn: 0.3002982 total: 17.1s remaining: 54.2s
246: learn: 0.3001609 total: 17.2s remaining: 54.2s
247: learn: 0.2998592 total: 17.3s remaining: 54.1s
248: learn: 0.2994256 total: 17.4s remaining: 54.1s
249: learn: 0.2993431 total: 17.4s remaining: 54s
250: learn: 0.2991535 total: 17.5s remaining: 53.9s
251: learn: 0.2987361 total: 17.6s remaining: 53.9s
252: learn: 0.2984622 total: 17.7s remaining: 53.8s
253: learn: 0.2981558 total: 17.7s remaining: 53.8s
254: learn: 0.2979213 total: 17.8s remaining: 53.7s
255: learn: 0.2977431 total: 17.9s remaining: 53.6s
256: learn: 0.2975592 total: 17.9s remaining: 53.6s
257: learn: 0.2974225 total: 18s remaining: 53.5s
258: learn: 0.2970970 total: 18.1s remaining: 53.4s
259: learn: 0.2967432 total: 18.1s remaining: 53.3s
260: learn: 0.2962776 total: 18.2s remaining: 53.2s
261: learn: 0.2961246 total: 18.3s remaining: 53.1s
262: learn: 0.2959562 total: 18.3s remaining: 53s
263: learn: 0.2957558 total: 18.4s remaining: 52.9s
264: learn: 0.2956696 total: 18.4s remaining: 52.8s
265: learn: 0.2954448 total: 18.5s remaining: 52.7s
266: learn: 0.2952793 total: 18.6s remaining: 52.7s
267: learn: 0.2951504 total: 18.7s remaining: 52.6s
268: learn: 0.2950694 total: 18.7s remaining: 52.6s
269: learn: 0.2948432 total: 18.8s remaining: 52.5s
270: learn: 0.2946433 total: 18.9s remaining: 52.4s
271: learn: 0.2944904 total: 18.9s remaining: 52.4s
272: learn: 0.2943346 total: 19s remaining: 52.3s
273: learn: 0.2942217 total: 19.1s remaining: 52.2s
274: learn: 0.2940400 total: 19.2s remaining: 52.2s
275: learn: 0.2938260 total: 19.2s remaining: 52.1s
276: learn: 0.2937586 total: 19.3s remaining: 52.1s
277: learn: 0.2936316 total: 19.4s remaining: 52s
278: learn: 0.2934571 total: 19.5s remaining: 52s
279: learn: 0.2933127 total: 19.5s remaining: 51.9s
280: learn: 0.2930690 total: 19.6s remaining: 51.8s
281: learn: 0.2929391 total: 19.7s remaining: 51.7s
282: learn: 0.2927437 total: 19.7s remaining: 51.7s
283: learn: 0.2925146 total: 19.8s remaining: 51.6s
284: learn: 0.2921039 total: 19.9s remaining: 51.5s
285: learn: 0.2919824 total: 19.9s remaining: 51.4s
286: learn: 0.2917051 total: 20s remaining: 51.4s
287: learn: 0.2914748 total: 20.1s remaining: 51.3s
288: learn: 0.2912332 total: 20.1s remaining: 51.2s
289: learn: 0.2909497 total: 20.2s remaining: 51.1s
290: learn: 0.2905744 total: 20.3s remaining: 51.1s
291: learn: 0.2902623 total: 20.3s remaining: 51s
292: learn: 0.2899594 total: 20.4s remaining: 50.9s
293: learn: 0.2896857 total: 20.5s remaining: 50.9s
294: learn: 0.2895054 total: 20.6s remaining: 50.8s
295: learn: 0.2891085 total: 20.6s remaining: 50.7s
296: learn: 0.2889078 total: 20.7s remaining: 50.7s
297: learn: 0.2887008 total: 20.8s remaining: 50.6s
298: learn: 0.2885392 total: 20.8s remaining: 50.5s
299: learn: 0.2883765 total: 20.9s remaining: 50.4s
300: learn: 0.2882007 total: 21s remaining: 50.3s
301: learn: 0.2881149 total: 21s remaining: 50.3s
302: learn: 0.2879924 total: 21.1s remaining: 50.2s
303: learn: 0.2878271 total: 21.2s remaining: 50.1s
304: learn: 0.2876889 total: 21.2s remaining: 50s
305: learn: 0.2875281 total: 21.3s remaining: 50s
306: learn: 0.2873258 total: 21.4s remaining: 49.9s
307: learn: 0.2872457 total: 21.4s remaining: 49.8s
308: learn: 0.2870524 total: 21.5s remaining: 49.7s
309: learn: 0.2868931 total: 21.6s remaining: 49.6s
310: learn: 0.2865974 total: 21.6s remaining: 49.6s
311: learn: 0.2863116 total: 21.7s remaining: 49.5s
312: learn: 0.2862594 total: 21.8s remaining: 49.4s
313: learn: 0.2861146 total: 21.8s remaining: 49.4s
314: learn: 0.2861137 total: 21.9s remaining: 49.2s
315: learn: 0.2857932 total: 21.9s remaining: 49.1s
316: learn: 0.2857616 total: 22s remaining: 49s
317: learn: 0.2855892 total: 22.1s remaining: 49s
318: learn: 0.2853528 total: 22.1s remaining: 48.9s
319: learn: 0.2850246 total: 22.2s remaining: 48.8s
320: learn: 0.2848713 total: 22.3s remaining: 48.7s
321: learn: 0.2846386 total: 22.3s remaining: 48.7s
322: learn: 0.2845065 total: 22.4s remaining: 48.6s
323: learn: 0.2843691 total: 22.5s remaining: 48.5s
324: learn: 0.2841419 total: 22.5s remaining: 48.4s
325: learn: 0.2838720 total: 22.6s remaining: 48.4s
326: learn: 0.2838710 total: 22.6s remaining: 48.2s
327: learn: 0.2836973 total: 22.7s remaining: 48.1s
328: learn: 0.2835608 total: 22.7s remaining: 48s
329: learn: 0.2833820 total: 22.8s remaining: 48s
330: learn: 0.2832751 total: 22.9s remaining: 47.9s
331: learn: 0.2830674 total: 22.9s remaining: 47.8s
332: learn: 0.2829220 total: 23s remaining: 47.8s
333: learn: 0.2826983 total: 23.1s remaining: 47.7s
334: learn: 0.2826225 total: 23.2s remaining: 47.7s
335: learn: 0.2825188 total: 23.3s remaining: 47.6s
336: learn: 0.2821985 total: 23.3s remaining: 47.6s
337: learn: 0.2818240 total: 23.4s remaining: 47.6s
338: learn: 0.2816214 total: 23.5s remaining: 47.5s
339: learn: 0.2814351 total: 23.6s remaining: 47.5s
340: learn: 0.2813059 total: 23.7s remaining: 47.5s
341: learn: 0.2811328 total: 23.8s remaining: 47.4s
342: learn: 0.2809717 total: 23.8s remaining: 47.4s
343: learn: 0.2807873 total: 23.9s remaining: 47.3s
344: learn: 0.2805148 total: 24s remaining: 47.3s
345: learn: 0.2802685 total: 24.1s remaining: 47.3s
346: learn: 0.2800161 total: 24.2s remaining: 47.2s
347: learn: 0.2799390 total: 24.3s remaining: 47.2s
348: learn: 0.2796649 total: 24.4s remaining: 47.1s
349: learn: 0.2795256 total: 24.5s remaining: 47.1s
350: learn: 0.2793865 total: 24.6s remaining: 47.1s
351: learn: 0.2791593 total: 24.6s remaining: 47s
352: learn: 0.2788704 total: 24.7s remaining: 47s
353: learn: 0.2786650 total: 24.8s remaining: 47s
354: learn: 0.2785567 total: 24.9s remaining: 46.9s
355: learn: 0.2782238 total: 25s remaining: 46.9s
356: learn: 0.2779395 total: 25.1s remaining: 46.8s
357: learn: 0.2776866 total: 25.1s remaining: 46.8s
358: learn: 0.2775965 total: 25.2s remaining: 46.8s
359: learn: 0.2772585 total: 25.3s remaining: 46.7s
360: learn: 0.2771102 total: 25.4s remaining: 46.7s
361: learn: 0.2769894 total: 25.5s remaining: 46.6s
362: learn: 0.2768474 total: 25.6s remaining: 46.6s
363: learn: 0.2766879 total: 25.7s remaining: 46.5s
364: learn: 0.2764757 total: 25.7s remaining: 46.5s
365: learn: 0.2763578 total: 25.8s remaining: 46.4s
366: learn: 0.2762510 total: 25.9s remaining: 46.4s
367: learn: 0.2760822 total: 26s remaining: 46.3s
368: learn: 0.2757728 total: 26.1s remaining: 46.3s
369: learn: 0.2756444 total: 26.1s remaining: 46.2s
370: learn: 0.2754629 total: 26.2s remaining: 46.2s
371: learn: 0.2754083 total: 26.3s remaining: 46.1s
372: learn: 0.2752087 total: 26.4s remaining: 46.1s
373: learn: 0.2750526 total: 26.5s remaining: 46s
374: learn: 0.2749698 total: 26.5s remaining: 45.9s
375: learn: 0.2749347 total: 26.6s remaining: 45.8s
376: learn: 0.2748489 total: 26.7s remaining: 45.8s
377: learn: 0.2746910 total: 26.7s remaining: 45.7s
378: learn: 0.2745636 total: 26.8s remaining: 45.6s
379: learn: 0.2743869 total: 26.9s remaining: 45.5s
380: learn: 0.2742662 total: 26.9s remaining: 45.4s
381: learn: 0.2740835 total: 27s remaining: 45.4s
382: learn: 0.2740057 total: 27.1s remaining: 45.3s
383: learn: 0.2738284 total: 27.1s remaining: 45.2s
384: learn: 0.2736510 total: 27.2s remaining: 45.1s
385: learn: 0.2735320 total: 27.3s remaining: 45.1s
386: learn: 0.2733809 total: 27.3s remaining: 45s
387: learn: 0.2732191 total: 27.4s remaining: 44.9s
388: learn: 0.2730874 total: 27.5s remaining: 44.8s
389: learn: 0.2729772 total: 27.5s remaining: 44.8s
390: learn: 0.2728087 total: 27.6s remaining: 44.7s
391: learn: 0.2724290 total: 27.7s remaining: 44.6s
392: learn: 0.2723179 total: 27.7s remaining: 44.5s
393: learn: 0.2722683 total: 27.8s remaining: 44.5s
394: learn: 0.2720805 total: 27.9s remaining: 44.4s
395: learn: 0.2720803 total: 27.9s remaining: 44.2s
396: learn: 0.2719036 total: 27.9s remaining: 44.1s
397: learn: 0.2717271 total: 28s remaining: 44.1s
398: learn: 0.2716627 total: 28.1s remaining: 44s
399: learn: 0.2715124 total: 28.1s remaining: 43.9s
400: learn: 0.2714924 total: 28.2s remaining: 43.8s
401: learn: 0.2712797 total: 28.3s remaining: 43.8s
402: learn: 0.2712481 total: 28.3s remaining: 43.7s
403: learn: 0.2710070 total: 28.4s remaining: 43.6s
404: learn: 0.2708781 total: 28.5s remaining: 43.5s
405: learn: 0.2705327 total: 28.5s remaining: 43.5s
406: learn: 0.2705325 total: 28.6s remaining: 43.3s
407: learn: 0.2701567 total: 28.6s remaining: 43.2s
408: learn: 0.2699658 total: 28.7s remaining: 43.2s
409: learn: 0.2697818 total: 28.8s remaining: 43.1s
410: learn: 0.2696457 total: 28.8s remaining: 43s
411: learn: 0.2694241 total: 28.9s remaining: 43s
412: learn: 0.2693222 total: 29s remaining: 42.9s
413: learn: 0.2691434 total: 29s remaining: 42.8s
414: learn: 0.2688690 total: 29.1s remaining: 42.7s
415: learn: 0.2686580 total: 29.2s remaining: 42.6s
416: learn: 0.2684506 total: 29.2s remaining: 42.6s
417: learn: 0.2683474 total: 29.3s remaining: 42.5s
418: learn: 0.2682301 total: 29.4s remaining: 42.4s
419: learn: 0.2680754 total: 29.4s remaining: 42.4s
420: learn: 0.2679772 total: 29.5s remaining: 42.3s
421: learn: 0.2679400 total: 29.6s remaining: 42.2s
422: learn: 0.2679340 total: 29.6s remaining: 42.1s
423: learn: 0.2678264 total: 29.7s remaining: 42s
424: learn: 0.2677129 total: 29.8s remaining: 41.9s
425: learn: 0.2675968 total: 29.8s remaining: 41.9s
426: learn: 0.2674502 total: 29.9s remaining: 41.8s
427: learn: 0.2672794 total: 30s remaining: 41.8s
428: learn: 0.2671029 total: 30.1s remaining: 41.7s
429: learn: 0.2670842 total: 30.2s remaining: 41.7s
430: learn: 0.2669307 total: 30.2s remaining: 41.6s
431: learn: 0.2667813 total: 30.3s remaining: 41.6s
432: learn: 0.2666442 total: 30.4s remaining: 41.5s
433: learn: 0.2664432 total: 30.5s remaining: 41.5s
434: learn: 0.2662543 total: 30.6s remaining: 41.4s
435: learn: 0.2661554 total: 30.7s remaining: 41.4s
436: learn: 0.2659858 total: 30.8s remaining: 41.3s
437: learn: 0.2658057 total: 30.8s remaining: 41.3s
438: learn: 0.2656284 total: 30.9s remaining: 41.2s
439: learn: 0.2654367 total: 31s remaining: 41.2s
440: learn: 0.2651511 total: 31.1s remaining: 41.1s
441: learn: 0.2651506 total: 31.1s remaining: 41s
442: learn: 0.2649327 total: 31.2s remaining: 40.9s
443: learn: 0.2649002 total: 31.3s remaining: 40.9s
444: learn: 0.2647970 total: 31.4s remaining: 40.8s
445: learn: 0.2645381 total: 31.5s remaining: 40.8s
446: learn: 0.2645003 total: 31.5s remaining: 40.7s
447: learn: 0.2643245 total: 31.6s remaining: 40.7s
448: learn: 0.2641570 total: 31.7s remaining: 40.6s
449: learn: 0.2638867 total: 31.8s remaining: 40.6s
450: learn: 0.2638864 total: 31.8s remaining: 40.5s
451: learn: 0.2638859 total: 31.9s remaining: 40.3s
452: learn: 0.2637424 total: 32s remaining: 40.3s
453: learn: 0.2635433 total: 32s remaining: 40.2s
454: learn: 0.2634013 total: 32.1s remaining: 40.2s
455: learn: 0.2632180 total: 32.2s remaining: 40.1s
456: learn: 0.2630770 total: 32.3s remaining: 40s
457: learn: 0.2628782 total: 32.4s remaining: 40s
458: learn: 0.2626975 total: 32.4s remaining: 39.9s
459: learn: 0.2625432 total: 32.5s remaining: 39.9s
460: learn: 0.2625033 total: 32.6s remaining: 39.8s
461: learn: 0.2623555 total: 32.7s remaining: 39.8s
462: learn: 0.2621588 total: 32.8s remaining: 39.7s
463: learn: 0.2619868 total: 32.9s remaining: 39.7s
464: learn: 0.2618653 total: 32.9s remaining: 39.6s
465: learn: 0.2616396 total: 33s remaining: 39.5s
466: learn: 0.2615636 total: 33.1s remaining: 39.5s
467: learn: 0.2614122 total: 33.2s remaining: 39.5s
468: learn: 0.2611618 total: 33.3s remaining: 39.4s
469: learn: 0.2610536 total: 33.4s remaining: 39.3s
470: learn: 0.2610127 total: 33.5s remaining: 39.3s
471: learn: 0.2609691 total: 33.5s remaining: 39.2s
472: learn: 0.2606600 total: 33.6s remaining: 39.1s
473: learn: 0.2606172 total: 33.7s remaining: 39.1s
474: learn: 0.2604705 total: 33.8s remaining: 39s
475: learn: 0.2603782 total: 33.8s remaining: 38.9s
476: learn: 0.2601344 total: 33.9s remaining: 38.9s
477: learn: 0.2600269 total: 34s remaining: 38.8s
478: learn: 0.2599593 total: 34s remaining: 38.7s
479: learn: 0.2598815 total: 34.1s remaining: 38.7s
480: learn: 0.2597620 total: 34.2s remaining: 38.6s
481: learn: 0.2596573 total: 34.2s remaining: 38.5s
482: learn: 0.2594560 total: 34.3s remaining: 38.5s
483: learn: 0.2593208 total: 34.4s remaining: 38.4s
484: learn: 0.2592667 total: 34.5s remaining: 38.3s
485: learn: 0.2591782 total: 34.5s remaining: 38.2s
486: learn: 0.2591353 total: 34.6s remaining: 38.2s
487: learn: 0.2590791 total: 34.7s remaining: 38.1s
488: learn: 0.2588753 total: 34.7s remaining: 38s
489: learn: 0.2588196 total: 34.8s remaining: 38s
490: learn: 0.2586221 total: 34.9s remaining: 37.9s
491: learn: 0.2583716 total: 35s remaining: 37.8s
492: learn: 0.2582524 total: 35s remaining: 37.7s
493: learn: 0.2581117 total: 35.1s remaining: 37.7s
494: learn: 0.2578460 total: 35.2s remaining: 37.6s
495: learn: 0.2575995 total: 35.2s remaining: 37.5s
496: learn: 0.2574463 total: 35.3s remaining: 37.4s
497: learn: 0.2573217 total: 35.4s remaining: 37.3s
498: learn: 0.2569365 total: 35.4s remaining: 37.3s
499: learn: 0.2567710 total: 35.5s remaining: 37.2s
500: learn: 0.2567289 total: 35.6s remaining: 37.2s
501: learn: 0.2565027 total: 35.7s remaining: 37.1s
502: learn: 0.2565023 total: 35.7s remaining: 37s
503: learn: 0.2565021 total: 35.7s remaining: 36.9s
504: learn: 0.2564114 total: 35.8s remaining: 36.8s
505: learn: 0.2562281 total: 35.9s remaining: 36.7s
506: learn: 0.2560348 total: 36s remaining: 36.7s
507: learn: 0.2558255 total: 36s remaining: 36.6s
508: learn: 0.2557211 total: 36.1s remaining: 36.5s
509: learn: 0.2554597 total: 36.2s remaining: 36.5s
510: learn: 0.2554162 total: 36.3s remaining: 36.4s
511: learn: 0.2553402 total: 36.3s remaining: 36.3s
512: learn: 0.2551779 total: 36.4s remaining: 36.3s
513: learn: 0.2550632 total: 36.5s remaining: 36.2s
514: learn: 0.2549443 total: 36.6s remaining: 36.1s
515: learn: 0.2547390 total: 36.6s remaining: 36.1s
516: learn: 0.2545609 total: 36.7s remaining: 36s
517: learn: 0.2544310 total: 36.8s remaining: 36s
518: learn: 0.2541818 total: 36.9s remaining: 35.9s
519: learn: 0.2541449 total: 37s remaining: 35.9s
520: learn: 0.2538869 total: 37.1s remaining: 35.8s
521: learn: 0.2537415 total: 37.2s remaining: 35.7s
522: learn: 0.2536469 total: 37.3s remaining: 35.7s
523: learn: 0.2534160 total: 37.3s remaining: 35.6s
524: learn: 0.2533382 total: 37.5s remaining: 35.6s
525: learn: 0.2532647 total: 37.6s remaining: 35.6s
526: learn: 0.2531813 total: 37.7s remaining: 35.5s
527: learn: 0.2531172 total: 37.8s remaining: 35.5s
528: learn: 0.2530260 total: 37.9s remaining: 35.4s
529: learn: 0.2528644 total: 38s remaining: 35.4s
530: learn: 0.2527463 total: 38.1s remaining: 35.4s
531: learn: 0.2526418 total: 38.2s remaining: 35.3s
532: learn: 0.2525114 total: 38.3s remaining: 35.3s
533: learn: 0.2521954 total: 38.4s remaining: 35.2s
534: learn: 0.2521640 total: 38.5s remaining: 35.2s
535: learn: 0.2520346 total: 38.6s remaining: 35.1s
536: learn: 0.2518133 total: 38.7s remaining: 35.1s
537: learn: 0.2517420 total: 38.8s remaining: 35s
538: learn: 0.2515123 total: 38.9s remaining: 35s
539: learn: 0.2512163 total: 39s remaining: 34.9s
540: learn: 0.2511068 total: 39.1s remaining: 34.9s
541: learn: 0.2510559 total: 39.2s remaining: 34.9s
542: learn: 0.2509483 total: 39.3s remaining: 34.8s
543: learn: 0.2508354 total: 39.4s remaining: 34.8s
544: learn: 0.2506462 total: 39.5s remaining: 34.7s
545: learn: 0.2504160 total: 39.6s remaining: 34.7s
546: learn: 0.2501104 total: 39.7s remaining: 34.6s
547: learn: 0.2499420 total: 39.8s remaining: 34.6s
548: learn: 0.2498732 total: 39.9s remaining: 34.5s
549: learn: 0.2497670 total: 40s remaining: 34.5s
550: learn: 0.2496307 total: 40.1s remaining: 34.4s
551: learn: 0.2496099 total: 40.2s remaining: 34.4s
552: learn: 0.2495725 total: 40.3s remaining: 34.3s
553: learn: 0.2495107 total: 40.4s remaining: 34.3s
554: learn: 0.2493644 total: 40.5s remaining: 34.3s
555: learn: 0.2492826 total: 40.6s remaining: 34.2s
556: learn: 0.2491372 total: 40.7s remaining: 34.1s
557: learn: 0.2489651 total: 40.8s remaining: 34.1s
558: learn: 0.2486844 total: 40.9s remaining: 34s
559: learn: 0.2485803 total: 41s remaining: 34s
560: learn: 0.2484793 total: 41.1s remaining: 33.9s
561: learn: 0.2483963 total: 41.2s remaining: 33.9s
562: learn: 0.2483199 total: 41.3s remaining: 33.8s
563: learn: 0.2482409 total: 41.4s remaining: 33.8s
564: learn: 0.2481374 total: 41.5s remaining: 33.7s
565: learn: 0.2479911 total: 41.5s remaining: 33.6s
566: learn: 0.2478756 total: 41.6s remaining: 33.6s
567: learn: 0.2477395 total: 41.7s remaining: 33.5s
568: learn: 0.2476877 total: 41.8s remaining: 33.4s
569: learn: 0.2474719 total: 41.9s remaining: 33.4s
570: learn: 0.2472514 total: 42s remaining: 33.3s
571: learn: 0.2471298 total: 42.1s remaining: 33.2s
572: learn: 0.2470058 total: 42.1s remaining: 33.2s
573: learn: 0.2469140 total: 42.2s remaining: 33.1s
574: learn: 0.2468478 total: 42.3s remaining: 33s
575: learn: 0.2465396 total: 42.4s remaining: 33s
576: learn: 0.2465243 total: 42.5s remaining: 32.9s
577: learn: 0.2464412 total: 42.5s remaining: 32.8s
578: learn: 0.2463313 total: 42.6s remaining: 32.8s
579: learn: 0.2463102 total: 42.7s remaining: 32.7s
580: learn: 0.2462087 total: 42.8s remaining: 32.6s
581: learn: 0.2461298 total: 42.9s remaining: 32.6s
582: learn: 0.2459474 total: 42.9s remaining: 32.5s
583: learn: 0.2458587 total: 43s remaining: 32.4s
584: learn: 0.2457655 total: 43.1s remaining: 32.3s
585: learn: 0.2456842 total: 43.2s remaining: 32.3s
586: learn: 0.2455273 total: 43.2s remaining: 32.2s
587: learn: 0.2453654 total: 43.4s remaining: 32.1s
588: learn: 0.2452173 total: 43.5s remaining: 32.1s
589: learn: 0.2450061 total: 43.5s remaining: 32s
590: learn: 0.2449043 total: 43.6s remaining: 32s
591: learn: 0.2448804 total: 43.7s remaining: 31.9s
592: learn: 0.2445964 total: 43.8s remaining: 31.8s
593: learn: 0.2444646 total: 43.9s remaining: 31.8s
594: learn: 0.2443250 total: 44s remaining: 31.7s
595: learn: 0.2441677 total: 44.1s remaining: 31.7s
596: learn: 0.2441675 total: 44.2s remaining: 31.6s
597: learn: 0.2441276 total: 44.3s remaining: 31.5s
598: learn: 0.2440487 total: 44.4s remaining: 31.5s
599: learn: 0.2439357 total: 44.5s remaining: 31.4s
600: learn: 0.2437799 total: 44.6s remaining: 31.4s
601: learn: 0.2437084 total: 44.7s remaining: 31.3s
602: learn: 0.2435455 total: 44.8s remaining: 31.3s
603: learn: 0.2434947 total: 44.9s remaining: 31.2s
604: learn: 0.2434169 total: 45s remaining: 31.2s
605: learn: 0.2433372 total: 45.1s remaining: 31.1s
606: learn: 0.2432564 total: 45.2s remaining: 31s
607: learn: 0.2431957 total: 45.3s remaining: 31s
608: learn: 0.2429769 total: 45.4s remaining: 30.9s
609: learn: 0.2429757 total: 45.4s remaining: 30.8s
610: learn: 0.2428502 total: 45.5s remaining: 30.8s
611: learn: 0.2427490 total: 45.6s remaining: 30.7s
612: learn: 0.2426779 total: 45.7s remaining: 30.7s
613: learn: 0.2425957 total: 45.8s remaining: 30.6s
614: learn: 0.2424731 total: 45.9s remaining: 30.5s
615: learn: 0.2423546 total: 46s remaining: 30.5s
616: learn: 0.2422987 total: 46.1s remaining: 30.4s
617: learn: 0.2421179 total: 46.2s remaining: 30.3s
618: learn: 0.2418788 total: 46.3s remaining: 30.3s
619: learn: 0.2416862 total: 46.4s remaining: 30.2s
620: learn: 0.2416854 total: 46.4s remaining: 30.1s
621: learn: 0.2415826 total: 46.5s remaining: 30s
622: learn: 0.2413957 total: 46.6s remaining: 30s
623: learn: 0.2413945 total: 46.6s remaining: 29.9s
624: learn: 0.2411411 total: 46.7s remaining: 29.8s
625: learn: 0.2409238 total: 46.8s remaining: 29.8s
626: learn: 0.2408082 total: 46.9s remaining: 29.7s
627: learn: 0.2406627 total: 47s remaining: 29.6s
628: learn: 0.2405579 total: 47.1s remaining: 29.5s
629: learn: 0.2405575 total: 47.1s remaining: 29.4s
630: learn: 0.2404382 total: 47.2s remaining: 29.4s
631: learn: 0.2403655 total: 47.2s remaining: 29.3s
632: learn: 0.2402002 total: 47.3s remaining: 29.2s
633: learn: 0.2401404 total: 47.4s remaining: 29.2s
634: learn: 0.2399751 total: 47.5s remaining: 29.1s
635: learn: 0.2398178 total: 47.6s remaining: 29s
636: learn: 0.2397030 total: 47.7s remaining: 29s
637: learn: 0.2395355 total: 47.7s remaining: 28.9s
638: learn: 0.2393410 total: 47.8s remaining: 28.8s
639: learn: 0.2392597 total: 47.9s remaining: 28.7s
640: learn: 0.2391777 total: 48s remaining: 28.7s
641: learn: 0.2390926 total: 48.1s remaining: 28.6s
642: learn: 0.2390915 total: 48.1s remaining: 28.5s
643: learn: 0.2390275 total: 48.2s remaining: 28.4s
644: learn: 0.2389084 total: 48.3s remaining: 28.4s
645: learn: 0.2388162 total: 48.3s remaining: 28.3s
646: learn: 0.2386433 total: 48.4s remaining: 28.2s
647: learn: 0.2384744 total: 48.5s remaining: 28.1s
648: learn: 0.2384489 total: 48.6s remaining: 28.1s
649: learn: 0.2383898 total: 48.7s remaining: 28s
650: learn: 0.2383433 total: 48.7s remaining: 27.9s
651: learn: 0.2381258 total: 48.8s remaining: 27.9s
652: learn: 0.2380629 total: 48.9s remaining: 27.8s
653: learn: 0.2379961 total: 49s remaining: 27.7s
654: learn: 0.2378967 total: 49.1s remaining: 27.6s
655: learn: 0.2377371 total: 49.1s remaining: 27.6s
656: learn: 0.2376758 total: 49.2s remaining: 27.5s
657: learn: 0.2374717 total: 49.3s remaining: 27.4s
658: learn: 0.2374713 total: 49.3s remaining: 27.3s
659: learn: 0.2373050 total: 49.3s remaining: 27.2s
660: learn: 0.2371309 total: 49.4s remaining: 27.1s
661: learn: 0.2371145 total: 49.5s remaining: 27.1s
662: learn: 0.2369864 total: 49.6s remaining: 27s
663: learn: 0.2369590 total: 49.6s remaining: 26.9s
664: learn: 0.2369234 total: 49.7s remaining: 26.8s
665: learn: 0.2368035 total: 49.7s remaining: 26.7s
666: learn: 0.2365430 total: 49.8s remaining: 26.7s
667: learn: 0.2363832 total: 49.9s remaining: 26.6s
668: learn: 0.2363822 total: 49.9s remaining: 26.5s
669: learn: 0.2362137 total: 50s remaining: 26.4s
670: learn: 0.2360995 total: 50s remaining: 26.3s
671: learn: 0.2360247 total: 50.1s remaining: 26.2s
672: learn: 0.2359032 total: 50.2s remaining: 26.2s
673: learn: 0.2358111 total: 50.2s remaining: 26.1s
674: learn: 0.2356487 total: 50.3s remaining: 26s
675: learn: 0.2355893 total: 50.4s remaining: 25.9s
676: learn: 0.2355151 total: 50.4s remaining: 25.9s
677: learn: 0.2353286 total: 50.5s remaining: 25.8s
678: learn: 0.2353112 total: 50.6s remaining: 25.7s
679: learn: 0.2353111 total: 50.6s remaining: 25.6s
680: learn: 0.2351663 total: 50.7s remaining: 25.5s
681: learn: 0.2351126 total: 50.7s remaining: 25.4s
682: learn: 0.2350471 total: 50.8s remaining: 25.4s
683: learn: 0.2348479 total: 50.9s remaining: 25.3s
684: learn: 0.2347689 total: 50.9s remaining: 25.2s
685: learn: 0.2345662 total: 51s remaining: 25.1s
686: learn: 0.2345235 total: 51.1s remaining: 25s
687: learn: 0.2343600 total: 51.1s remaining: 25s
688: learn: 0.2342663 total: 51.2s remaining: 24.9s
689: learn: 0.2342073 total: 51.3s remaining: 24.8s
690: learn: 0.2342022 total: 51.3s remaining: 24.7s
691: learn: 0.2340888 total: 51.4s remaining: 24.6s
692: learn: 0.2340537 total: 51.4s remaining: 24.6s
693: learn: 0.2339687 total: 51.5s remaining: 24.5s
694: learn: 0.2339413 total: 51.6s remaining: 24.4s
695: learn: 0.2337402 total: 51.6s remaining: 24.3s
696: learn: 0.2336879 total: 51.7s remaining: 24.3s
697: learn: 0.2335148 total: 51.8s remaining: 24.2s
698: learn: 0.2333821 total: 51.8s remaining: 24.1s
699: learn: 0.2333259 total: 51.9s remaining: 24s
700: learn: 0.2332947 total: 52s remaining: 23.9s
701: learn: 0.2332250 total: 52s remaining: 23.9s
702: learn: 0.2332012 total: 52.1s remaining: 23.8s
703: learn: 0.2331136 total: 52.2s remaining: 23.7s
704: learn: 0.2330622 total: 52.2s remaining: 23.6s
705: learn: 0.2329400 total: 52.3s remaining: 23.6s
706: learn: 0.2328741 total: 52.4s remaining: 23.5s
707: learn: 0.2327239 total: 52.4s remaining: 23.4s
708: learn: 0.2326275 total: 52.5s remaining: 23.3s
709: learn: 0.2324744 total: 52.6s remaining: 23.3s
710: learn: 0.2322592 total: 52.7s remaining: 23.2s
711: learn: 0.2321018 total: 52.8s remaining: 23.1s
712: learn: 0.2320248 total: 52.9s remaining: 23.1s
713: learn: 0.2318980 total: 52.9s remaining: 23s
714: learn: 0.2318811 total: 53s remaining: 22.9s
715: learn: 0.2318798 total: 53.1s remaining: 22.8s
716: learn: 0.2318222 total: 53.2s remaining: 22.8s
717: learn: 0.2316491 total: 53.2s remaining: 22.7s
718: learn: 0.2316379 total: 53.3s remaining: 22.6s
719: learn: 0.2315974 total: 53.4s remaining: 22.5s
720: learn: 0.2315973 total: 53.4s remaining: 22.4s
721: learn: 0.2314718 total: 53.5s remaining: 22.4s
722: learn: 0.2314285 total: 53.6s remaining: 22.3s
723: learn: 0.2311934 total: 53.7s remaining: 22.2s
724: learn: 0.2310925 total: 53.8s remaining: 22.2s
725: learn: 0.2310375 total: 53.8s remaining: 22.1s
726: learn: 0.2310335 total: 53.9s remaining: 22s
727: learn: 0.2309819 total: 54s remaining: 21.9s
728: learn: 0.2309819 total: 54s remaining: 21.8s
729: learn: 0.2308321 total: 54.1s remaining: 21.8s
730: learn: 0.2307612 total: 54.2s remaining: 21.7s
731: learn: 0.2307611 total: 54.2s remaining: 21.6s
732: learn: 0.2306006 total: 54.3s remaining: 21.5s
733: learn: 0.2305249 total: 54.4s remaining: 21.5s
734: learn: 0.2305020 total: 54.4s remaining: 21.4s
735: learn: 0.2304358 total: 54.5s remaining: 21.3s
736: learn: 0.2303340 total: 54.6s remaining: 21.3s
737: learn: 0.2300296 total: 54.7s remaining: 21.2s
738: learn: 0.2300156 total: 54.8s remaining: 21.1s
739: learn: 0.2298677 total: 54.9s remaining: 21.1s
740: learn: 0.2296151 total: 55s remaining: 21s
741: learn: 0.2295153 total: 55.1s remaining: 20.9s
742: learn: 0.2294212 total: 55.1s remaining: 20.9s
743: learn: 0.2293586 total: 55.2s remaining: 20.8s
744: learn: 0.2291869 total: 55.3s remaining: 20.7s
745: learn: 0.2291160 total: 55.4s remaining: 20.6s
746: learn: 0.2291159 total: 55.4s remaining: 20.6s
747: learn: 0.2290362 total: 55.5s remaining: 20.5s
748: learn: 0.2289781 total: 55.6s remaining: 20.4s
749: learn: 0.2288064 total: 55.7s remaining: 20.3s
750: learn: 0.2287899 total: 55.7s remaining: 20.3s
751: learn: 0.2286987 total: 55.8s remaining: 20.2s
752: learn: 0.2285947 total: 55.9s remaining: 20.1s
753: learn: 0.2284063 total: 56s remaining: 20.1s
754: learn: 0.2282731 total: 56.1s remaining: 20s
755: learn: 0.2281361 total: 56.2s remaining: 19.9s
756: learn: 0.2279392 total: 56.3s remaining: 19.8s
757: learn: 0.2277941 total: 56.3s remaining: 19.8s
758: learn: 0.2277696 total: 56.4s remaining: 19.7s
759: learn: 0.2275648 total: 56.5s remaining: 19.6s
760: learn: 0.2275151 total: 56.6s remaining: 19.6s
761: learn: 0.2275066 total: 56.7s remaining: 19.5s
762: learn: 0.2273860 total: 56.7s remaining: 19.4s
763: learn: 0.2272397 total: 56.8s remaining: 19.3s
764: learn: 0.2271215 total: 56.9s remaining: 19.3s
765: learn: 0.2270178 total: 57s remaining: 19.2s
766: learn: 0.2269450 total: 57.1s remaining: 19.1s
767: learn: 0.2268724 total: 57.1s remaining: 19s
768: learn: 0.2267698 total: 57.2s remaining: 19s
769: learn: 0.2266552 total: 57.3s remaining: 18.9s
770: learn: 0.2264403 total: 57.4s remaining: 18.8s
771: learn: 0.2263611 total: 57.5s remaining: 18.8s
772: learn: 0.2262221 total: 57.6s remaining: 18.7s
773: learn: 0.2260974 total: 57.6s remaining: 18.6s
774: learn: 0.2259972 total: 57.7s remaining: 18.5s
775: learn: 0.2259560 total: 57.8s remaining: 18.5s
776: learn: 0.2258579 total: 57.9s remaining: 18.4s
777: learn: 0.2257761 total: 58s remaining: 18.3s
778: learn: 0.2256252 total: 58s remaining: 18.3s
779: learn: 0.2254904 total: 58.1s remaining: 18.2s
780: learn: 0.2254132 total: 58.2s remaining: 18.1s
781: learn: 0.2254129 total: 58.2s remaining: 18s
782: learn: 0.2252810 total: 58.3s remaining: 17.9s
783: learn: 0.2251704 total: 58.5s remaining: 17.9s
784: learn: 0.2249395 total: 58.6s remaining: 17.8s
785: learn: 0.2248665 total: 58.6s remaining: 17.8s
786: learn: 0.2247280 total: 58.7s remaining: 17.7s
787: learn: 0.2247262 total: 58.7s remaining: 17.6s
788: learn: 0.2246879 total: 58.8s remaining: 17.5s
789: learn: 0.2246191 total: 58.9s remaining: 17.4s
790: learn: 0.2245245 total: 59s remaining: 17.4s
791: learn: 0.2244440 total: 59.1s remaining: 17.3s
792: learn: 0.2242069 total: 59.1s remaining: 17.2s
793: learn: 0.2240382 total: 59.2s remaining: 17.2s
794: learn: 0.2240047 total: 59.3s remaining: 17.1s
795: learn: 0.2238969 total: 59.4s remaining: 17s
796: learn: 0.2237958 total: 59.4s remaining: 16.9s
797: learn: 0.2237952 total: 59.5s remaining: 16.8s
798: learn: 0.2235774 total: 59.5s remaining: 16.8s
799: learn: 0.2234162 total: 59.6s remaining: 16.7s
800: learn: 0.2232900 total: 59.6s remaining: 16.6s
801: learn: 0.2230551 total: 59.7s remaining: 16.5s
802: learn: 0.2229532 total: 59.8s remaining: 16.5s
803: learn: 0.2229304 total: 59.8s remaining: 16.4s
804: learn: 0.2228251 total: 59.9s remaining: 16.3s
805: learn: 0.2227221 total: 60s remaining: 16.2s
806: learn: 0.2227133 total: 1m remaining: 16.1s
807: learn: 0.2226096 total: 1m remaining: 16.1s
808: learn: 0.2225784 total: 1m remaining: 16s
809: learn: 0.2224807 total: 1m remaining: 15.9s
810: learn: 0.2224558 total: 1m remaining: 15.8s
811: learn: 0.2222446 total: 1m remaining: 15.8s
812: learn: 0.2222058 total: 1m remaining: 15.7s
813: learn: 0.2220584 total: 1m remaining: 15.6s
814: learn: 0.2219152 total: 1m remaining: 15.5s
815: learn: 0.2216600 total: 1m remaining: 15.5s
816: learn: 0.2216095 total: 1m remaining: 15.4s
817: learn: 0.2213282 total: 1m remaining: 15.3s
818: learn: 0.2211919 total: 1m remaining: 15.2s
819: learn: 0.2211013 total: 1m remaining: 15.1s
820: learn: 0.2208942 total: 1m remaining: 15.1s
821: learn: 0.2208137 total: 1m 1s remaining: 15s
822: learn: 0.2206538 total: 1m 1s remaining: 14.9s
823: learn: 0.2205374 total: 1m 1s remaining: 14.8s
824: learn: 0.2204575 total: 1m 1s remaining: 14.8s
825: learn: 0.2203071 total: 1m 1s remaining: 14.7s
826: learn: 0.2201478 total: 1m 1s remaining: 14.6s
827: learn: 0.2201476 total: 1m 1s remaining: 14.5s
828: learn: 0.2200709 total: 1m 1s remaining: 14.4s
829: learn: 0.2200020 total: 1m 1s remaining: 14.4s
830: learn: 0.2199227 total: 1m 1s remaining: 14.3s
831: learn: 0.2198017 total: 1m 1s remaining: 14.2s
832: learn: 0.2197361 total: 1m 1s remaining: 14.1s
833: learn: 0.2196050 total: 1m 1s remaining: 14.1s
834: learn: 0.2193851 total: 1m 1s remaining: 14s
835: learn: 0.2193030 total: 1m 1s remaining: 13.9s
836: learn: 0.2192361 total: 1m 1s remaining: 13.8s
837: learn: 0.2191973 total: 1m 2s remaining: 13.8s
838: learn: 0.2190760 total: 1m 2s remaining: 13.7s
839: learn: 0.2190459 total: 1m 2s remaining: 13.6s
840: learn: 0.2190447 total: 1m 2s remaining: 13.5s
841: learn: 0.2189479 total: 1m 2s remaining: 13.4s
842: learn: 0.2189193 total: 1m 2s remaining: 13.4s
843: learn: 0.2189077 total: 1m 2s remaining: 13.3s
844: learn: 0.2187765 total: 1m 2s remaining: 13.2s
845: learn: 0.2186610 total: 1m 2s remaining: 13.1s
846: learn: 0.2186609 total: 1m 2s remaining: 13.1s
847: learn: 0.2186335 total: 1m 2s remaining: 13s
848: learn: 0.2186126 total: 1m 2s remaining: 12.9s
849: learn: 0.2184522 total: 1m 2s remaining: 12.8s
850: learn: 0.2182835 total: 1m 2s remaining: 12.8s
851: learn: 0.2181646 total: 1m 2s remaining: 12.7s
852: learn: 0.2180986 total: 1m 2s remaining: 12.6s
853: learn: 0.2180975 total: 1m 3s remaining: 12.5s
854: learn: 0.2179103 total: 1m 3s remaining: 12.5s
855: learn: 0.2178116 total: 1m 3s remaining: 12.4s
856: learn: 0.2177339 total: 1m 3s remaining: 12.3s
857: learn: 0.2175229 total: 1m 3s remaining: 12.3s
858: learn: 0.2174415 total: 1m 3s remaining: 12.2s
859: learn: 0.2173377 total: 1m 3s remaining: 12.1s
860: learn: 0.2172614 total: 1m 3s remaining: 12s
861: learn: 0.2171448 total: 1m 3s remaining: 12s
862: learn: 0.2170894 total: 1m 3s remaining: 11.9s
863: learn: 0.2170560 total: 1m 3s remaining: 11.8s
864: learn: 0.2168856 total: 1m 3s remaining: 11.7s
865: learn: 0.2168853 total: 1m 3s remaining: 11.7s
866: learn: 0.2168378 total: 1m 4s remaining: 11.6s
867: learn: 0.2165939 total: 1m 4s remaining: 11.5s
868: learn: 0.2164416 total: 1m 4s remaining: 11.4s
869: learn: 0.2163757 total: 1m 4s remaining: 11.4s
870: learn: 0.2162659 total: 1m 4s remaining: 11.3s
871: learn: 0.2161685 total: 1m 4s remaining: 11.2s
872: learn: 0.2159767 total: 1m 4s remaining: 11.2s
873: learn: 0.2159107 total: 1m 4s remaining: 11.1s
874: learn: 0.2157123 total: 1m 4s remaining: 11s
875: learn: 0.2156025 total: 1m 4s remaining: 10.9s
876: learn: 0.2155059 total: 1m 4s remaining: 10.9s
877: learn: 0.2154487 total: 1m 4s remaining: 10.8s
878: learn: 0.2154190 total: 1m 5s remaining: 10.7s
879: learn: 0.2151784 total: 1m 5s remaining: 10.7s
880: learn: 0.2151140 total: 1m 5s remaining: 10.6s
881: learn: 0.2150751 total: 1m 5s remaining: 10.5s
882: learn: 0.2150226 total: 1m 5s remaining: 10.4s
883: learn: 0.2149266 total: 1m 5s remaining: 10.4s
884: learn: 0.2147507 total: 1m 5s remaining: 10.3s
885: learn: 0.2146096 total: 1m 5s remaining: 10.2s
886: learn: 0.2145336 total: 1m 5s remaining: 10.1s
887: learn: 0.2145327 total: 1m 5s remaining: 10.1s
888: learn: 0.2144193 total: 1m 5s remaining: 9.99s
889: learn: 0.2143948 total: 1m 5s remaining: 9.91s
890: learn: 0.2141860 total: 1m 5s remaining: 9.84s
891: learn: 0.2140523 total: 1m 6s remaining: 9.77s
892: learn: 0.2140424 total: 1m 6s remaining: 9.7s
893: learn: 0.2140419 total: 1m 6s remaining: 9.62s
894: learn: 0.2139962 total: 1m 6s remaining: 9.54s
895: learn: 0.2138567 total: 1m 6s remaining: 9.47s
896: learn: 0.2138043 total: 1m 6s remaining: 9.4s
897: learn: 0.2137307 total: 1m 6s remaining: 9.33s
898: learn: 0.2135675 total: 1m 6s remaining: 9.25s
899: learn: 0.2134598 total: 1m 6s remaining: 9.18s
900: learn: 0.2134211 total: 1m 6s remaining: 9.11s
901: learn: 0.2133310 total: 1m 6s remaining: 9.03s
902: learn: 0.2132856 total: 1m 6s remaining: 8.96s
903: learn: 0.2132113 total: 1m 6s remaining: 8.89s
904: learn: 0.2131363 total: 1m 7s remaining: 8.81s
905: learn: 0.2130631 total: 1m 7s remaining: 8.74s
906: learn: 0.2129668 total: 1m 7s remaining: 8.67s
907: learn: 0.2129537 total: 1m 7s remaining: 8.6s
908: learn: 0.2127518 total: 1m 7s remaining: 8.52s
909: learn: 0.2126823 total: 1m 7s remaining: 8.45s
910: learn: 0.2126777 total: 1m 7s remaining: 8.37s
911: learn: 0.2125960 total: 1m 7s remaining: 8.3s
912: learn: 0.2124816 total: 1m 7s remaining: 8.23s
913: learn: 0.2124287 total: 1m 7s remaining: 8.15s
914: learn: 0.2124276 total: 1m 7s remaining: 8.08s
915: learn: 0.2123215 total: 1m 7s remaining: 8s
916: learn: 0.2122016 total: 1m 7s remaining: 7.93s
917: learn: 0.2121766 total: 1m 8s remaining: 7.86s
918: learn: 0.2120518 total: 1m 8s remaining: 7.78s
919: learn: 0.2119306 total: 1m 8s remaining: 7.71s
920: learn: 0.2117721 total: 1m 8s remaining: 7.64s
921: learn: 0.2117072 total: 1m 8s remaining: 7.56s
922: learn: 0.2115308 total: 1m 8s remaining: 7.49s
923: learn: 0.2114755 total: 1m 8s remaining: 7.42s
924: learn: 0.2111438 total: 1m 8s remaining: 7.34s
925: learn: 0.2109436 total: 1m 8s remaining: 7.27s
926: learn: 0.2108452 total: 1m 8s remaining: 7.2s
927: learn: 0.2106284 total: 1m 8s remaining: 7.12s
928: learn: 0.2105345 total: 1m 8s remaining: 7.05s
929: learn: 0.2103725 total: 1m 9s remaining: 6.98s
930: learn: 0.2103719 total: 1m 9s remaining: 6.9s
931: learn: 0.2103655 total: 1m 9s remaining: 6.82s
932: learn: 0.2103378 total: 1m 9s remaining: 6.75s
933: learn: 0.2102915 total: 1m 9s remaining: 6.68s
934: learn: 0.2102037 total: 1m 9s remaining: 6.6s
935: learn: 0.2100724 total: 1m 9s remaining: 6.53s
936: learn: 0.2099714 total: 1m 9s remaining: 6.46s
937: learn: 0.2099216 total: 1m 9s remaining: 6.38s
938: learn: 0.2098372 total: 1m 9s remaining: 6.31s
939: learn: 0.2097964 total: 1m 9s remaining: 6.24s
940: learn: 0.2097533 total: 1m 9s remaining: 6.16s
941: learn: 0.2096614 total: 1m 9s remaining: 6.09s
942: learn: 0.2096608 total: 1m 10s remaining: 6.01s
943: learn: 0.2095976 total: 1m 10s remaining: 5.94s
944: learn: 0.2095971 total: 1m 10s remaining: 5.86s
945: learn: 0.2094815 total: 1m 10s remaining: 5.79s
946: learn: 0.2093913 total: 1m 10s remaining: 5.71s
947: learn: 0.2093673 total: 1m 10s remaining: 5.64s
948: learn: 0.2093403 total: 1m 10s remaining: 5.57s
949: learn: 0.2091605 total: 1m 10s remaining: 5.49s
950: learn: 0.2090957 total: 1m 10s remaining: 5.42s
951: learn: 0.2089864 total: 1m 10s remaining: 5.35s
952: learn: 0.2089855 total: 1m 10s remaining: 5.27s
953: learn: 0.2089582 total: 1m 10s remaining: 5.2s
954: learn: 0.2089043 total: 1m 10s remaining: 5.12s
955: learn: 0.2088090 total: 1m 10s remaining: 5.05s
956: learn: 0.2087022 total: 1m 11s remaining: 4.97s
957: learn: 0.2086151 total: 1m 11s remaining: 4.9s
958: learn: 0.2085870 total: 1m 11s remaining: 4.83s
959: learn: 0.2084953 total: 1m 11s remaining: 4.75s
960: learn: 0.2083624 total: 1m 11s remaining: 4.68s
961: learn: 0.2082889 total: 1m 11s remaining: 4.61s
962: learn: 0.2082290 total: 1m 11s remaining: 4.53s
963: learn: 0.2082277 total: 1m 11s remaining: 4.46s
964: learn: 0.2081131 total: 1m 11s remaining: 4.38s
965: learn: 0.2079752 total: 1m 11s remaining: 4.31s
966: learn: 0.2078807 total: 1m 11s remaining: 4.24s
967: learn: 0.2077531 total: 1m 11s remaining: 4.16s
968: learn: 0.2077527 total: 1m 11s remaining: 4.08s
969: learn: 0.2076463 total: 1m 12s remaining: 4.01s
970: learn: 0.2076452 total: 1m 12s remaining: 3.94s
971: learn: 0.2075288 total: 1m 12s remaining: 3.86s
972: learn: 0.2073913 total: 1m 12s remaining: 3.79s
973: learn: 0.2072985 total: 1m 12s remaining: 3.71s
974: learn: 0.2072155 total: 1m 12s remaining: 3.64s
975: learn: 0.2071110 total: 1m 12s remaining: 3.56s
976: learn: 0.2070175 total: 1m 12s remaining: 3.49s
977: learn: 0.2069245 total: 1m 12s remaining: 3.42s
978: learn: 0.2069133 total: 1m 12s remaining: 3.34s
979: learn: 0.2068641 total: 1m 12s remaining: 3.27s
980: learn: 0.2068135 total: 1m 12s remaining: 3.19s
981: learn: 0.2067782 total: 1m 12s remaining: 3.12s
982: learn: 0.2067765 total: 1m 13s remaining: 3.04s
983: learn: 0.2067401 total: 1m 13s remaining: 2.97s
984: learn: 0.2066670 total: 1m 13s remaining: 2.9s
985: learn: 0.2066634 total: 1m 13s remaining: 2.82s
986: learn: 0.2066627 total: 1m 13s remaining: 2.75s
987: learn: 0.2065720 total: 1m 13s remaining: 2.67s
988: learn: 0.2063699 total: 1m 13s remaining: 2.6s
989: learn: 0.2062493 total: 1m 13s remaining: 2.52s
990: learn: 0.2061236 total: 1m 13s remaining: 2.45s
991: learn: 0.2060276 total: 1m 13s remaining: 2.38s
992: learn: 0.2058254 total: 1m 13s remaining: 2.3s
993: learn: 0.2057950 total: 1m 13s remaining: 2.23s
994: learn: 0.2057541 total: 1m 13s remaining: 2.15s
995: learn: 0.2056768 total: 1m 13s remaining: 2.08s
996: learn: 0.2055585 total: 1m 14s remaining: 2s
997: learn: 0.2055049 total: 1m 14s remaining: 1.93s
998: learn: 0.2054486 total: 1m 14s remaining: 1.86s
999: learn: 0.2053777 total: 1m 14s remaining: 1.78s
1000: learn: 0.2052720 total: 1m 14s remaining: 1.71s
1001: learn: 0.2052484 total: 1m 14s remaining: 1.63s
1002: learn: 0.2051834 total: 1m 14s remaining: 1.56s
1003: learn: 0.2051438 total: 1m 14s remaining: 1.49s
1004: learn: 0.2049943 total: 1m 14s remaining: 1.41s
1005: learn: 0.2048826 total: 1m 14s remaining: 1.34s
1006: learn: 0.2048379 total: 1m 14s remaining: 1.26s
1007: learn: 0.2047978 total: 1m 14s remaining: 1.19s
1008: learn: 0.2047630 total: 1m 15s remaining: 1.11s
1009: learn: 0.2046512 total: 1m 15s remaining: 1.04s
1010: learn: 0.2046505 total: 1m 15s remaining: 966ms
1011: learn: 0.2045644 total: 1m 15s remaining: 892ms
1012: learn: 0.2044870 total: 1m 15s remaining: 818ms
1013: learn: 0.2044496 total: 1m 15s remaining: 743ms
1014: learn: 0.2044016 total: 1m 15s remaining: 669ms
1015: learn: 0.2043694 total: 1m 15s remaining: 595ms
1016: learn: 0.2043396 total: 1m 15s remaining: 520ms
1017: learn: 0.2042074 total: 1m 15s remaining: 446ms
1018: learn: 0.2041256 total: 1m 15s remaining: 372ms
1019: learn: 0.2040450 total: 1m 15s remaining: 298ms
1020: learn: 0.2040450 total: 1m 15s remaining: 223ms
1021: learn: 0.2039529 total: 1m 15s remaining: 149ms
1022: learn: 0.2038499 total: 1m 16s remaining: 74.3ms
1023: learn: 0.2038017 total: 1m 16s remaining: 0us
Out[105]:
<catboost.core.CatBoostClassifier at 0x247933b1978>
In [111]:
preds = model.predict_proba(X_stack_test)[:,1]
In [86]:
X_stack_train.shape, X_stack_test.shape
Out[86]:
((18359, 12), (15021, 12))
In [91]:
m = RandomForestClassifier(n_estimators=200,max_features=0.5, n_jobs=-1, oob_score=True)
m.fit(X_stack_train, target)
Out[91]:
RandomForestClassifier(bootstrap=True, class_weight=None, criterion='gini',
max_depth=None, max_features=0.5, max_leaf_nodes=None,
min_impurity_decrease=0.0, min_impurity_split=None,
min_samples_leaf=1, min_samples_split=2,
min_weight_fraction_leaf=0.0, n_estimators=200, n_jobs=-1,
oob_score=True, random_state=None, verbose=0, warm_start=False)
In [92]:
preds
Out[92]:
array([ 0.86975, 0.02263, 0.39715, ..., 0.06079, 0.18257, 0.06129])
In [95]:
preds_rf = m.predict_proba(X_stack_test)[:, 1]
In [97]:
import xgboost as xgb
import gc, mlcrate
In [100]:
%%time
N_COMP = 10
print("\nStart decomposition process...")
print("PCA")
pca = PCA(n_components=N_COMP, random_state=17)
pca_results_X_train = pca.fit_transform(X_stack_train)
pca_results_X_test = pca.transform(X_stack_test)
Start decomposition process...
PCA
Wall time: 652 ms
In [103]:
%%time
print("Append decomposition components to datasets...")
for i in range(1, N_COMP + 1):
X_train_num['pca_' + str(i)] = pca_results_X_train[:, i - 1]
X_test_num['pca_' + str(i)] = pca_results_X_test[:, i - 1]
Append decomposition components to datasets...
Wall time: 19.5 ms
In [108]:
2425/(2425+15934)
Out[108]:
0.13208780434664197
In [107]:
np.bincount(target)
Out[107]:
array([15934, 2425], dtype=int64)
In [75]:
params = {}
params['booster'] = 'gbtree'
params["objective"] = "binary:logistic"
# params['eval_metric'] = 'logloss'
params['eval_metric'] = 'auc'
params["eta"] = 0.05 #0.03
params["subsample"] = .85 #.85 was tried before
params["silent"] = 0
params['verbose'] = 1
params["max_depth"] = 9
params["seed"] = 1
params["max_delta_step"] = 4
params['scale_pos_weight'] = 0.13208780434664197
params["gamma"] = 1.0 #.5 #.1 #.2
params['colsample_bytree'] = 0.9
params['nrounds'] = 1000 #3600 #2000 #4000 #using lower no for demo
#params['max_leaves'] = 511
#params['verbose_eval'] = 50
In [128]:
submit = make_submission(p_test)
submit.to_csv(f'{PATH}\\AV_Stud_2\\xgb_depth_9.csv', index=False)
submit.head(2)
Out[128]:
enrollee_id
target
0
16548
0.127784
1
12036
0.011873
In [76]:
model_xgb, p_train, p_test = mlcrate.xgb.train_kfold(params, X_stack_train, target, X_stack_test\
, folds = 7,skip_checks = True, stratify=target, print_imp='final')
[mlcrate] Training 7 stratified XGBoost models on training set (18359, 22) with test set (15021, 22)
[mlcrate] Running fold 0, 15735 train samples, 2624 validation samples
[0] train-auc:0.579363 valid-auc:0.571273
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.585361 valid-auc:0.57603
[2] train-auc:0.585361 valid-auc:0.57603
[3] train-auc:0.585361 valid-auc:0.57603
[4] train-auc:0.594184 valid-auc:0.581385
[5] train-auc:0.594184 valid-auc:0.581385
[6] train-auc:0.594184 valid-auc:0.581385
[7] train-auc:0.594186 valid-auc:0.581443
[8] train-auc:0.594186 valid-auc:0.581443
[9] train-auc:0.594191 valid-auc:0.581432
[10] train-auc:0.594191 valid-auc:0.581432
[11] train-auc:0.594885 valid-auc:0.582977
[12] train-auc:0.594902 valid-auc:0.583005
[13] train-auc:0.595196 valid-auc:0.582943
[14] train-auc:0.595207 valid-auc:0.582946
[15] train-auc:0.595226 valid-auc:0.583045
[16] train-auc:0.649343 valid-auc:0.646431
[17] train-auc:0.649148 valid-auc:0.646527
[18] train-auc:0.649129 valid-auc:0.646479
[19] train-auc:0.648933 valid-auc:0.646183
[20] train-auc:0.650184 valid-auc:0.648182
[21] train-auc:0.65012 valid-auc:0.648137
[22] train-auc:0.650097 valid-auc:0.648063
[23] train-auc:0.654736 valid-auc:0.651182
[24] train-auc:0.654643 valid-auc:0.651208
[25] train-auc:0.65562 valid-auc:0.651559
[26] train-auc:0.657359 valid-auc:0.65164
[27] train-auc:0.658165 valid-auc:0.654741
[28] train-auc:0.659723 valid-auc:0.654604
[29] train-auc:0.659669 valid-auc:0.655506
[30] train-auc:0.659772 valid-auc:0.655803
[31] train-auc:0.660039 valid-auc:0.655461
[32] train-auc:0.660395 valid-auc:0.655487
[33] train-auc:0.659682 valid-auc:0.655689
[34] train-auc:0.659774 valid-auc:0.655906
[35] train-auc:0.66267 valid-auc:0.658003
[36] train-auc:0.663068 valid-auc:0.657718
[37] train-auc:0.663172 valid-auc:0.658027
[38] train-auc:0.663886 valid-auc:0.658292
[39] train-auc:0.66439 valid-auc:0.658586
[40] train-auc:0.665747 valid-auc:0.658787
[41] train-auc:0.666603 valid-auc:0.658961
[42] train-auc:0.667311 valid-auc:0.659031
[43] train-auc:0.667071 valid-auc:0.658953
[44] train-auc:0.667532 valid-auc:0.658555
[45] train-auc:0.669817 valid-auc:0.658505
[46] train-auc:0.670373 valid-auc:0.658959
[47] train-auc:0.6705 valid-auc:0.658784
[48] train-auc:0.670936 valid-auc:0.65899
[49] train-auc:0.671203 valid-auc:0.65852
[50] train-auc:0.673582 valid-auc:0.663165
[51] train-auc:0.676313 valid-auc:0.664597
[52] train-auc:0.677545 valid-auc:0.666452
[53] train-auc:0.677721 valid-auc:0.666412
[54] train-auc:0.678805 valid-auc:0.666422
[55] train-auc:0.678863 valid-auc:0.667165
[56] train-auc:0.679019 valid-auc:0.666912
[57] train-auc:0.67972 valid-auc:0.668003
[58] train-auc:0.681118 valid-auc:0.669511
[59] train-auc:0.682038 valid-auc:0.669137
[60] train-auc:0.68285 valid-auc:0.669431
[61] train-auc:0.683069 valid-auc:0.66958
[62] train-auc:0.683858 valid-auc:0.669047
[63] train-auc:0.685733 valid-auc:0.669715
[64] train-auc:0.686524 valid-auc:0.669852
[65] train-auc:0.68732 valid-auc:0.66971
[66] train-auc:0.688247 valid-auc:0.670195
[67] train-auc:0.690928 valid-auc:0.673913
[68] train-auc:0.698423 valid-auc:0.672159
[69] train-auc:0.698847 valid-auc:0.671953
[70] train-auc:0.699466 valid-auc:0.671252
[71] train-auc:0.703895 valid-auc:0.670295
[72] train-auc:0.706417 valid-auc:0.670154
[73] train-auc:0.709407 valid-auc:0.671212
[74] train-auc:0.709947 valid-auc:0.672456
[75] train-auc:0.710429 valid-auc:0.672115
[76] train-auc:0.711806 valid-auc:0.672142
[77] train-auc:0.713072 valid-auc:0.671611
[78] train-auc:0.713086 valid-auc:0.671266
[79] train-auc:0.713301 valid-auc:0.671382
[80] train-auc:0.713505 valid-auc:0.67099
[81] train-auc:0.716542 valid-auc:0.670595
[82] train-auc:0.718128 valid-auc:0.670908
[83] train-auc:0.719265 valid-auc:0.670702
[84] train-auc:0.720825 valid-auc:0.672394
[85] train-auc:0.722469 valid-auc:0.672938
[86] train-auc:0.723663 valid-auc:0.673185
[87] train-auc:0.724702 valid-auc:0.673737
[88] train-auc:0.725637 valid-auc:0.673826
[89] train-auc:0.725701 valid-auc:0.673999
[90] train-auc:0.727236 valid-auc:0.67399
[91] train-auc:0.729874 valid-auc:0.675717
[92] train-auc:0.73162 valid-auc:0.676617
[93] train-auc:0.73438 valid-auc:0.675086
[94] train-auc:0.735972 valid-auc:0.677114
[95] train-auc:0.735892 valid-auc:0.676415
[96] train-auc:0.737478 valid-auc:0.676574
[97] train-auc:0.73808 valid-auc:0.676108
[98] train-auc:0.738866 valid-auc:0.675971
[99] train-auc:0.740181 valid-auc:0.674128
[100] train-auc:0.740768 valid-auc:0.673742
[101] train-auc:0.742062 valid-auc:0.673457
[102] train-auc:0.742793 valid-auc:0.674167
[103] train-auc:0.743766 valid-auc:0.67354
[104] train-auc:0.744633 valid-auc:0.673183
[105] train-auc:0.746553 valid-auc:0.673073
[106] train-auc:0.748868 valid-auc:0.673401
[107] train-auc:0.751 valid-auc:0.672642
[108] train-auc:0.75191 valid-auc:0.672001
[109] train-auc:0.753374 valid-auc:0.671394
[110] train-auc:0.755044 valid-auc:0.671928
[111] train-auc:0.755343 valid-auc:0.671755
[112] train-auc:0.756461 valid-auc:0.67122
[113] train-auc:0.758118 valid-auc:0.671288
[114] train-auc:0.758739 valid-auc:0.671728
[115] train-auc:0.759854 valid-auc:0.671758
[116] train-auc:0.760731 valid-auc:0.671352
[117] train-auc:0.761923 valid-auc:0.671167
[118] train-auc:0.762582 valid-auc:0.671581
[119] train-auc:0.763335 valid-auc:0.671108
[120] train-auc:0.764053 valid-auc:0.671487
[121] train-auc:0.764195 valid-auc:0.671371
[122] train-auc:0.765064 valid-auc:0.671341
[123] train-auc:0.765869 valid-auc:0.671169
[124] train-auc:0.76684 valid-auc:0.671289
[125] train-auc:0.767645 valid-auc:0.671084
[126] train-auc:0.768745 valid-auc:0.67018
[127] train-auc:0.769566 valid-auc:0.670028
[128] train-auc:0.770967 valid-auc:0.669805
[129] train-auc:0.771459 valid-auc:0.670181
[130] train-auc:0.772441 valid-auc:0.670252
[131] train-auc:0.773079 valid-auc:0.669117
[132] train-auc:0.773419 valid-auc:0.669412
[133] train-auc:0.774734 valid-auc:0.669276
[134] train-auc:0.775381 valid-auc:0.669102
[135] train-auc:0.776146 valid-auc:0.668604
[136] train-auc:0.776665 valid-auc:0.668799
[137] train-auc:0.77702 valid-auc:0.668831
[138] train-auc:0.777982 valid-auc:0.66908
[139] train-auc:0.778248 valid-auc:0.66885
[140] train-auc:0.779318 valid-auc:0.668875
[141] train-auc:0.780037 valid-auc:0.668035
[142] train-auc:0.780472 valid-auc:0.66771
[143] train-auc:0.780815 valid-auc:0.667737
[144] train-auc:0.781552 valid-auc:0.667779
Stopping. Best iteration:
[94] train-auc:0.735972 valid-auc:0.677114
C:\ProgramData\Anaconda3\lib\site-packages\mlcrate\backend.py:7: UserWarning: Timer.format_elapsed() has been deprecated in favour of Timer.fsince() and will be removed soon
warn(message)
[mlcrate] Finished training fold 0 - took 7s - running score 0.677114
[mlcrate] Running fold 1, 15735 train samples, 2624 validation samples
[0] train-auc:0.5 valid-auc:0.5
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.5 valid-auc:0.5
[2] train-auc:0.577177 valid-auc:0.59677
[3] train-auc:0.579448 valid-auc:0.599072
[4] train-auc:0.579448 valid-auc:0.599074
[5] train-auc:0.579448 valid-auc:0.599074
[6] train-auc:0.595003 valid-auc:0.605398
[7] train-auc:0.595244 valid-auc:0.606562
[8] train-auc:0.595244 valid-auc:0.606562
[9] train-auc:0.595253 valid-auc:0.606838
[10] train-auc:0.595253 valid-auc:0.606838
[11] train-auc:0.595228 valid-auc:0.607948
[12] train-auc:0.595264 valid-auc:0.608207
[13] train-auc:0.595729 valid-auc:0.608362
[14] train-auc:0.595737 valid-auc:0.60842
[15] train-auc:0.595741 valid-auc:0.60841
[16] train-auc:0.596053 valid-auc:0.608676
[17] train-auc:0.596063 valid-auc:0.608772
[18] train-auc:0.596453 valid-auc:0.608815
[19] train-auc:0.596453 valid-auc:0.608815
[20] train-auc:0.596583 valid-auc:0.608813
[21] train-auc:0.598297 valid-auc:0.606795
[22] train-auc:0.598236 valid-auc:0.606678
[23] train-auc:0.646166 valid-auc:0.666086
[24] train-auc:0.64618 valid-auc:0.666288
[25] train-auc:0.647582 valid-auc:0.668354
[26] train-auc:0.648738 valid-auc:0.670505
[27] train-auc:0.648719 valid-auc:0.670343
[28] train-auc:0.649128 valid-auc:0.670812
[29] train-auc:0.650453 valid-auc:0.67273
[30] train-auc:0.653344 valid-auc:0.675567
[31] train-auc:0.65471 valid-auc:0.676982
[32] train-auc:0.657395 valid-auc:0.673468
[33] train-auc:0.658107 valid-auc:0.673753
[34] train-auc:0.658552 valid-auc:0.673954
[35] train-auc:0.659692 valid-auc:0.676023
[36] train-auc:0.662049 valid-auc:0.678025
[37] train-auc:0.662641 valid-auc:0.679348
[38] train-auc:0.662466 valid-auc:0.678943
[39] train-auc:0.662535 valid-auc:0.679733
[40] train-auc:0.662666 valid-auc:0.679956
[41] train-auc:0.662762 valid-auc:0.680224
[42] train-auc:0.664045 valid-auc:0.680234
[43] train-auc:0.663946 valid-auc:0.679653
[44] train-auc:0.664861 valid-auc:0.679576
[45] train-auc:0.666695 valid-auc:0.680234
[46] train-auc:0.667662 valid-auc:0.680687
[47] train-auc:0.667702 valid-auc:0.680263
[48] train-auc:0.668006 valid-auc:0.680328
[49] train-auc:0.668501 valid-auc:0.680659
[50] train-auc:0.670655 valid-auc:0.680332
[51] train-auc:0.670541 valid-auc:0.680517
[52] train-auc:0.671554 valid-auc:0.680268
[53] train-auc:0.673326 valid-auc:0.681383
[54] train-auc:0.674251 valid-auc:0.682114
[55] train-auc:0.674974 valid-auc:0.681607
[56] train-auc:0.675101 valid-auc:0.682521
[57] train-auc:0.676038 valid-auc:0.682483
[58] train-auc:0.680291 valid-auc:0.685219
[59] train-auc:0.68094 valid-auc:0.685109
[60] train-auc:0.683343 valid-auc:0.685218
[61] train-auc:0.685785 valid-auc:0.687191
[62] train-auc:0.686255 valid-auc:0.687651
[63] train-auc:0.687851 valid-auc:0.688167
[64] train-auc:0.68829 valid-auc:0.688539
[65] train-auc:0.690828 valid-auc:0.692013
[66] train-auc:0.69123 valid-auc:0.691648
[67] train-auc:0.692173 valid-auc:0.691355
[68] train-auc:0.693052 valid-auc:0.693175
[69] train-auc:0.694747 valid-auc:0.692542
[70] train-auc:0.696433 valid-auc:0.692526
[71] train-auc:0.697965 valid-auc:0.691786
[72] train-auc:0.698559 valid-auc:0.692319
[73] train-auc:0.699884 valid-auc:0.692773
[74] train-auc:0.701125 valid-auc:0.693191
[75] train-auc:0.703 valid-auc:0.693163
[76] train-auc:0.70334 valid-auc:0.692874
[77] train-auc:0.704715 valid-auc:0.693443
[78] train-auc:0.706902 valid-auc:0.693153
[79] train-auc:0.708692 valid-auc:0.694483
[80] train-auc:0.709615 valid-auc:0.694661
[81] train-auc:0.712187 valid-auc:0.69298
[82] train-auc:0.712906 valid-auc:0.692812
[83] train-auc:0.714024 valid-auc:0.693828
[84] train-auc:0.714875 valid-auc:0.693814
[85] train-auc:0.71718 valid-auc:0.694842
[86] train-auc:0.718194 valid-auc:0.694838
[87] train-auc:0.719846 valid-auc:0.694132
[88] train-auc:0.720379 valid-auc:0.694744
[89] train-auc:0.722243 valid-auc:0.695427
[90] train-auc:0.723651 valid-auc:0.695112
[91] train-auc:0.724271 valid-auc:0.694892
[92] train-auc:0.724682 valid-auc:0.695497
[93] train-auc:0.724819 valid-auc:0.695346
[94] train-auc:0.726739 valid-auc:0.694958
[95] train-auc:0.727615 valid-auc:0.694759
[96] train-auc:0.728421 valid-auc:0.69487
[97] train-auc:0.73012 valid-auc:0.694498
[98] train-auc:0.730728 valid-auc:0.694561
[99] train-auc:0.732711 valid-auc:0.694407
[100] train-auc:0.734646 valid-auc:0.693637
[101] train-auc:0.735801 valid-auc:0.693016
[102] train-auc:0.736716 valid-auc:0.692886
[103] train-auc:0.737911 valid-auc:0.692991
[104] train-auc:0.739161 valid-auc:0.693814
[105] train-auc:0.740049 valid-auc:0.693897
[106] train-auc:0.740764 valid-auc:0.692737
[107] train-auc:0.741719 valid-auc:0.69185
[108] train-auc:0.742272 valid-auc:0.692527
[109] train-auc:0.743298 valid-auc:0.693188
[110] train-auc:0.743873 valid-auc:0.69311
[111] train-auc:0.744341 valid-auc:0.692967
[112] train-auc:0.745141 valid-auc:0.692755
[113] train-auc:0.746627 valid-auc:0.692
[114] train-auc:0.747429 valid-auc:0.692444
[115] train-auc:0.748162 valid-auc:0.69231
[116] train-auc:0.749506 valid-auc:0.69215
[117] train-auc:0.750602 valid-auc:0.691893
[118] train-auc:0.751863 valid-auc:0.691553
[119] train-auc:0.752881 valid-auc:0.69064
[120] train-auc:0.75411 valid-auc:0.691303
[121] train-auc:0.75493 valid-auc:0.691817
[122] train-auc:0.755948 valid-auc:0.691372
[123] train-auc:0.756035 valid-auc:0.691221
[124] train-auc:0.757646 valid-auc:0.691062
[125] train-auc:0.758246 valid-auc:0.690811
[126] train-auc:0.759496 valid-auc:0.691303
[127] train-auc:0.76104 valid-auc:0.690825
[128] train-auc:0.762016 valid-auc:0.690469
[129] train-auc:0.763122 valid-auc:0.690287
[130] train-auc:0.763502 valid-auc:0.690404
[131] train-auc:0.764314 valid-auc:0.690608
[132] train-auc:0.764831 valid-auc:0.690862
[133] train-auc:0.765468 valid-auc:0.690945
[134] train-auc:0.766729 valid-auc:0.69182
[135] train-auc:0.767563 valid-auc:0.692027
[136] train-auc:0.768154 valid-auc:0.692324
[137] train-auc:0.769015 valid-auc:0.692307
[138] train-auc:0.769608 valid-auc:0.692022
[139] train-auc:0.770426 valid-auc:0.692599
[140] train-auc:0.771882 valid-auc:0.692917
[141] train-auc:0.772725 valid-auc:0.692498
[142] train-auc:0.773182 valid-auc:0.692474
Stopping. Best iteration:
[92] train-auc:0.724682 valid-auc:0.695497
[mlcrate] Finished training fold 1 - took 7s - running score 0.6863055
[mlcrate] Running fold 2, 15736 train samples, 2623 validation samples
[0] train-auc:0.5 valid-auc:0.5
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.5 valid-auc:0.5
[2] train-auc:0.575752 valid-auc:0.594618
[3] train-auc:0.58004 valid-auc:0.597841
[4] train-auc:0.580224 valid-auc:0.597852
[5] train-auc:0.586076 valid-auc:0.604532
[6] train-auc:0.586076 valid-auc:0.604532
[7] train-auc:0.586196 valid-auc:0.604195
[8] train-auc:0.586196 valid-auc:0.604195
[9] train-auc:0.586196 valid-auc:0.604195
[10] train-auc:0.587541 valid-auc:0.602599
[11] train-auc:0.587541 valid-auc:0.602599
[12] train-auc:0.587719 valid-auc:0.602744
[13] train-auc:0.589489 valid-auc:0.602627
[14] train-auc:0.589489 valid-auc:0.602627
[15] train-auc:0.642637 valid-auc:0.651837
[16] train-auc:0.643049 valid-auc:0.652062
[17] train-auc:0.642926 valid-auc:0.652072
[18] train-auc:0.642951 valid-auc:0.652069
[19] train-auc:0.647811 valid-auc:0.659317
[20] train-auc:0.647636 valid-auc:0.659411
[21] train-auc:0.648731 valid-auc:0.658046
[22] train-auc:0.649539 valid-auc:0.657273
[23] train-auc:0.650094 valid-auc:0.658795
[24] train-auc:0.653645 valid-auc:0.670306
[25] train-auc:0.655794 valid-auc:0.67182
[26] train-auc:0.655911 valid-auc:0.6709
[27] train-auc:0.655827 valid-auc:0.670724
[28] train-auc:0.659211 valid-auc:0.672093
[29] train-auc:0.659101 valid-auc:0.671909
[30] train-auc:0.659721 valid-auc:0.671433
[31] train-auc:0.660945 valid-auc:0.669886
[32] train-auc:0.661662 valid-auc:0.671902
[33] train-auc:0.66209 valid-auc:0.67209
[34] train-auc:0.662352 valid-auc:0.67229
[35] train-auc:0.662291 valid-auc:0.672323
[36] train-auc:0.662486 valid-auc:0.673068
[37] train-auc:0.662594 valid-auc:0.672785
[38] train-auc:0.664149 valid-auc:0.673563
[39] train-auc:0.664329 valid-auc:0.673579
[40] train-auc:0.664461 valid-auc:0.67448
[41] train-auc:0.66487 valid-auc:0.674474
[42] train-auc:0.665136 valid-auc:0.673744
[43] train-auc:0.665499 valid-auc:0.673803
[44] train-auc:0.665182 valid-auc:0.674248
[45] train-auc:0.666534 valid-auc:0.674993
[46] train-auc:0.667214 valid-auc:0.674711
[47] train-auc:0.667437 valid-auc:0.674629
[48] train-auc:0.667367 valid-auc:0.67468
[49] train-auc:0.667595 valid-auc:0.675145
[50] train-auc:0.669462 valid-auc:0.677406
[51] train-auc:0.671449 valid-auc:0.677819
[52] train-auc:0.671346 valid-auc:0.677886
[53] train-auc:0.672242 valid-auc:0.678481
[54] train-auc:0.672123 valid-auc:0.678022
[55] train-auc:0.672818 valid-auc:0.678535
[56] train-auc:0.673508 valid-auc:0.678776
[57] train-auc:0.674231 valid-auc:0.678622
[58] train-auc:0.674516 valid-auc:0.678251
[59] train-auc:0.678774 valid-auc:0.678912
[60] train-auc:0.678766 valid-auc:0.679226
[61] train-auc:0.67979 valid-auc:0.683644
[62] train-auc:0.685762 valid-auc:0.684377
[63] train-auc:0.686399 valid-auc:0.684204
[64] train-auc:0.686663 valid-auc:0.683288
[65] train-auc:0.689963 valid-auc:0.684216
[66] train-auc:0.691092 valid-auc:0.684777
[67] train-auc:0.691347 valid-auc:0.68462
[68] train-auc:0.695423 valid-auc:0.686399
[69] train-auc:0.696497 valid-auc:0.686607
[70] train-auc:0.696684 valid-auc:0.686884
[71] train-auc:0.699006 valid-auc:0.687105
[72] train-auc:0.700049 valid-auc:0.687173
[73] train-auc:0.701102 valid-auc:0.688389
[74] train-auc:0.701407 valid-auc:0.68847
[75] train-auc:0.702337 valid-auc:0.688989
[76] train-auc:0.705491 valid-auc:0.691798
[77] train-auc:0.706068 valid-auc:0.691208
[78] train-auc:0.707378 valid-auc:0.691382
[79] train-auc:0.709776 valid-auc:0.690402
[80] train-auc:0.711121 valid-auc:0.690464
[81] train-auc:0.712354 valid-auc:0.691074
[82] train-auc:0.713532 valid-auc:0.690837
[83] train-auc:0.715064 valid-auc:0.691401
[84] train-auc:0.715823 valid-auc:0.691208
[85] train-auc:0.716135 valid-auc:0.691805
[86] train-auc:0.717516 valid-auc:0.691148
[87] train-auc:0.718897 valid-auc:0.691229
[88] train-auc:0.719224 valid-auc:0.691097
[89] train-auc:0.720247 valid-auc:0.691269
[90] train-auc:0.720934 valid-auc:0.691403
[91] train-auc:0.721594 valid-auc:0.691584
[92] train-auc:0.722308 valid-auc:0.691593
[93] train-auc:0.722942 valid-auc:0.691453
[94] train-auc:0.723632 valid-auc:0.691439
[95] train-auc:0.725741 valid-auc:0.691067
[96] train-auc:0.726299 valid-auc:0.691638
[97] train-auc:0.726782 valid-auc:0.690765
[98] train-auc:0.727896 valid-auc:0.691601
[99] train-auc:0.728555 valid-auc:0.691236
[100] train-auc:0.730601 valid-auc:0.691347
[101] train-auc:0.730985 valid-auc:0.691636
[102] train-auc:0.73281 valid-auc:0.691725
[103] train-auc:0.733751 valid-auc:0.690927
[104] train-auc:0.734671 valid-auc:0.691848
[105] train-auc:0.735283 valid-auc:0.692167
[106] train-auc:0.736182 valid-auc:0.692277
[107] train-auc:0.737082 valid-auc:0.691995
[108] train-auc:0.73778 valid-auc:0.692067
[109] train-auc:0.738588 valid-auc:0.692535
[110] train-auc:0.740176 valid-auc:0.692539
[111] train-auc:0.741011 valid-auc:0.693371
[112] train-auc:0.741772 valid-auc:0.693401
[113] train-auc:0.742525 valid-auc:0.693436
[114] train-auc:0.743586 valid-auc:0.693965
[115] train-auc:0.74424 valid-auc:0.693519
[116] train-auc:0.745536 valid-auc:0.694383
[117] train-auc:0.746165 valid-auc:0.694739
[118] train-auc:0.747842 valid-auc:0.694956
[119] train-auc:0.748276 valid-auc:0.695031
[120] train-auc:0.749057 valid-auc:0.69478
[121] train-auc:0.749811 valid-auc:0.695717
[122] train-auc:0.75043 valid-auc:0.695115
[123] train-auc:0.750711 valid-auc:0.694779
[124] train-auc:0.75221 valid-auc:0.694228
[125] train-auc:0.753022 valid-auc:0.694023
[126] train-auc:0.754556 valid-auc:0.694034
[127] train-auc:0.755686 valid-auc:0.69385
[128] train-auc:0.75723 valid-auc:0.69319
[129] train-auc:0.757782 valid-auc:0.693447
[130] train-auc:0.758187 valid-auc:0.693591
[131] train-auc:0.759149 valid-auc:0.693545
[132] train-auc:0.760357 valid-auc:0.693534
[133] train-auc:0.761961 valid-auc:0.694079
[134] train-auc:0.762404 valid-auc:0.693403
[135] train-auc:0.763574 valid-auc:0.693377
[136] train-auc:0.764196 valid-auc:0.693024
[137] train-auc:0.7645 valid-auc:0.692834
[138] train-auc:0.765293 valid-auc:0.693268
[139] train-auc:0.76549 valid-auc:0.693063
[140] train-auc:0.766121 valid-auc:0.692716
[141] train-auc:0.766731 valid-auc:0.693042
[142] train-auc:0.767641 valid-auc:0.692559
[143] train-auc:0.768591 valid-auc:0.692114
[144] train-auc:0.76996 valid-auc:0.692736
[145] train-auc:0.771284 valid-auc:0.692723
[146] train-auc:0.771655 valid-auc:0.692572
[147] train-auc:0.772379 valid-auc:0.691941
[148] train-auc:0.773109 valid-auc:0.691872
[149] train-auc:0.773591 valid-auc:0.691819
[150] train-auc:0.774 valid-auc:0.691568
[151] train-auc:0.774563 valid-auc:0.691488
[152] train-auc:0.775204 valid-auc:0.690851
[153] train-auc:0.775459 valid-auc:0.691102
[154] train-auc:0.77593 valid-auc:0.691135
[155] train-auc:0.776787 valid-auc:0.691007
[156] train-auc:0.777007 valid-auc:0.69147
[157] train-auc:0.77771 valid-auc:0.691767
[158] train-auc:0.778518 valid-auc:0.692074
[159] train-auc:0.779438 valid-auc:0.6916
[160] train-auc:0.780594 valid-auc:0.692163
[161] train-auc:0.781592 valid-auc:0.692456
[162] train-auc:0.782317 valid-auc:0.692594
[163] train-auc:0.782734 valid-auc:0.692756
[164] train-auc:0.782907 valid-auc:0.692738
[165] train-auc:0.783306 valid-auc:0.69261
[166] train-auc:0.783681 valid-auc:0.691972
[167] train-auc:0.783729 valid-auc:0.691753
[168] train-auc:0.784399 valid-auc:0.691691
[169] train-auc:0.785033 valid-auc:0.691931
[170] train-auc:0.785271 valid-auc:0.691658
[171] train-auc:0.787042 valid-auc:0.692065
Stopping. Best iteration:
[121] train-auc:0.749811 valid-auc:0.695717
[mlcrate] Finished training fold 2 - took 9s - running score 0.6894426666666668
[mlcrate] Running fold 3, 15737 train samples, 2622 validation samples
[0] train-auc:0.588072 valid-auc:0.559539
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.589141 valid-auc:0.560326
[2] train-auc:0.58914 valid-auc:0.560266
[3] train-auc:0.589148 valid-auc:0.560268
[4] train-auc:0.589148 valid-auc:0.560268
[5] train-auc:0.589148 valid-auc:0.560268
[6] train-auc:0.589148 valid-auc:0.560268
[7] train-auc:0.589148 valid-auc:0.560268
[8] train-auc:0.590097 valid-auc:0.561932
[9] train-auc:0.593031 valid-auc:0.569522
[10] train-auc:0.592843 valid-auc:0.57471
[11] train-auc:0.593049 valid-auc:0.574647
[12] train-auc:0.593093 valid-auc:0.574652
[13] train-auc:0.595983 valid-auc:0.576094
[14] train-auc:0.596087 valid-auc:0.576094
[15] train-auc:0.596057 valid-auc:0.576094
[16] train-auc:0.59605 valid-auc:0.576094
[17] train-auc:0.596006 valid-auc:0.576094
[18] train-auc:0.616019 valid-auc:0.589628
[19] train-auc:0.658676 valid-auc:0.622753
[20] train-auc:0.658705 valid-auc:0.622753
[21] train-auc:0.658424 valid-auc:0.623466
[22] train-auc:0.658962 valid-auc:0.623942
[23] train-auc:0.659274 valid-auc:0.626883
[24] train-auc:0.659707 valid-auc:0.627418
[25] train-auc:0.65981 valid-auc:0.627592
[26] train-auc:0.659502 valid-auc:0.627692
[27] train-auc:0.661124 valid-auc:0.62539
[28] train-auc:0.660676 valid-auc:0.625098
[29] train-auc:0.661964 valid-auc:0.624043
[30] train-auc:0.663446 valid-auc:0.624771
[31] train-auc:0.66455 valid-auc:0.624988
[32] train-auc:0.663791 valid-auc:0.628446
[33] train-auc:0.666666 valid-auc:0.629283
[34] train-auc:0.667262 valid-auc:0.628337
[35] train-auc:0.667547 valid-auc:0.628664
[36] train-auc:0.66747 valid-auc:0.628394
[37] train-auc:0.668332 valid-auc:0.627508
[38] train-auc:0.668858 valid-auc:0.626062
[39] train-auc:0.669415 valid-auc:0.625675
[40] train-auc:0.669126 valid-auc:0.625415
[41] train-auc:0.669267 valid-auc:0.625473
[42] train-auc:0.669824 valid-auc:0.625506
[43] train-auc:0.670373 valid-auc:0.626619
[44] train-auc:0.670668 valid-auc:0.627144
[45] train-auc:0.671686 valid-auc:0.628315
[46] train-auc:0.672817 valid-auc:0.62807
[47] train-auc:0.678175 valid-auc:0.634511
[48] train-auc:0.679672 valid-auc:0.636167
[49] train-auc:0.680058 valid-auc:0.63589
[50] train-auc:0.682068 valid-auc:0.63632
[51] train-auc:0.682721 valid-auc:0.636039
[52] train-auc:0.684952 valid-auc:0.639215
[53] train-auc:0.684977 valid-auc:0.639411
[54] train-auc:0.686812 valid-auc:0.639445
[55] train-auc:0.689352 valid-auc:0.639672
[56] train-auc:0.690192 valid-auc:0.639259
[57] train-auc:0.690995 valid-auc:0.6393
[58] train-auc:0.691623 valid-auc:0.638922
[59] train-auc:0.692889 valid-auc:0.639185
[60] train-auc:0.693885 valid-auc:0.639937
[61] train-auc:0.695553 valid-auc:0.635241
[62] train-auc:0.695802 valid-auc:0.635394
[63] train-auc:0.69848 valid-auc:0.640526
[64] train-auc:0.698913 valid-auc:0.639742
[65] train-auc:0.700357 valid-auc:0.641735
[66] train-auc:0.700587 valid-auc:0.642159
[67] train-auc:0.701459 valid-auc:0.642796
[68] train-auc:0.701992 valid-auc:0.642123
[69] train-auc:0.702762 valid-auc:0.642066
[70] train-auc:0.702862 valid-auc:0.642212
[71] train-auc:0.70376 valid-auc:0.64153
[72] train-auc:0.704771 valid-auc:0.642904
[73] train-auc:0.706998 valid-auc:0.643481
[74] train-auc:0.709577 valid-auc:0.642008
[75] train-auc:0.71065 valid-auc:0.642098
[76] train-auc:0.711815 valid-auc:0.641294
[77] train-auc:0.714167 valid-auc:0.640111
[78] train-auc:0.714668 valid-auc:0.640421
[79] train-auc:0.717341 valid-auc:0.641939
[80] train-auc:0.718695 valid-auc:0.641587
[81] train-auc:0.719325 valid-auc:0.641733
[82] train-auc:0.719966 valid-auc:0.642262
[83] train-auc:0.721654 valid-auc:0.643154
[84] train-auc:0.722669 valid-auc:0.643295
[85] train-auc:0.724511 valid-auc:0.642743
[86] train-auc:0.726738 valid-auc:0.643135
[87] train-auc:0.727088 valid-auc:0.642389
[88] train-auc:0.728057 valid-auc:0.642947
[89] train-auc:0.729158 valid-auc:0.644064
[90] train-auc:0.729727 valid-auc:0.644632
[91] train-auc:0.730351 valid-auc:0.644652
[92] train-auc:0.731951 valid-auc:0.644799
[93] train-auc:0.733124 valid-auc:0.644048
[94] train-auc:0.733537 valid-auc:0.643925
[95] train-auc:0.735502 valid-auc:0.643626
[96] train-auc:0.736322 valid-auc:0.642631
[97] train-auc:0.736964 valid-auc:0.642883
[98] train-auc:0.737475 valid-auc:0.643354
[99] train-auc:0.738495 valid-auc:0.642982
[100] train-auc:0.73961 valid-auc:0.643303
[101] train-auc:0.74048 valid-auc:0.642672
[102] train-auc:0.741682 valid-auc:0.642236
[103] train-auc:0.74315 valid-auc:0.642264
[104] train-auc:0.744273 valid-auc:0.64194
[105] train-auc:0.745262 valid-auc:0.641375
[106] train-auc:0.747075 valid-auc:0.641417
[107] train-auc:0.747717 valid-auc:0.641973
[108] train-auc:0.749126 valid-auc:0.641444
[109] train-auc:0.750784 valid-auc:0.641855
[110] train-auc:0.752136 valid-auc:0.642244
[111] train-auc:0.753743 valid-auc:0.642648
[112] train-auc:0.754394 valid-auc:0.64303
[113] train-auc:0.756517 valid-auc:0.642438
[114] train-auc:0.757125 valid-auc:0.642845
[115] train-auc:0.757992 valid-auc:0.642282
[116] train-auc:0.758772 valid-auc:0.642526
[117] train-auc:0.759726 valid-auc:0.643247
[118] train-auc:0.760467 valid-auc:0.643057
[119] train-auc:0.762109 valid-auc:0.643938
[120] train-auc:0.763231 valid-auc:0.643622
[121] train-auc:0.763809 valid-auc:0.643695
[122] train-auc:0.764351 valid-auc:0.6435
[123] train-auc:0.764671 valid-auc:0.643595
[124] train-auc:0.765686 valid-auc:0.642764
[125] train-auc:0.765945 valid-auc:0.643099
[126] train-auc:0.766591 valid-auc:0.643171
[127] train-auc:0.767683 valid-auc:0.643199
[128] train-auc:0.768604 valid-auc:0.643099
[129] train-auc:0.769098 valid-auc:0.643797
[130] train-auc:0.769463 valid-auc:0.644279
[131] train-auc:0.770606 valid-auc:0.643092
[132] train-auc:0.771508 valid-auc:0.642991
[133] train-auc:0.771991 valid-auc:0.643263
[134] train-auc:0.773423 valid-auc:0.643517
[135] train-auc:0.77408 valid-auc:0.644681
[136] train-auc:0.774802 valid-auc:0.644745
[137] train-auc:0.775372 valid-auc:0.644834
[138] train-auc:0.776054 valid-auc:0.645069
[139] train-auc:0.776009 valid-auc:0.645539
[140] train-auc:0.776221 valid-auc:0.645177
[141] train-auc:0.778148 valid-auc:0.644807
[142] train-auc:0.779727 valid-auc:0.645344
[143] train-auc:0.780698 valid-auc:0.64502
[144] train-auc:0.781371 valid-auc:0.645005
[145] train-auc:0.782164 valid-auc:0.645098
[146] train-auc:0.783133 valid-auc:0.644303
[147] train-auc:0.783604 valid-auc:0.643674
[148] train-auc:0.784378 valid-auc:0.643781
[149] train-auc:0.785622 valid-auc:0.643464
[150] train-auc:0.786319 valid-auc:0.64337
[151] train-auc:0.78728 valid-auc:0.643786
[152] train-auc:0.787864 valid-auc:0.643466
[153] train-auc:0.788322 valid-auc:0.643601
[154] train-auc:0.789958 valid-auc:0.643678
[155] train-auc:0.791645 valid-auc:0.642986
[156] train-auc:0.792625 valid-auc:0.642977
[157] train-auc:0.793629 valid-auc:0.64321
[158] train-auc:0.794009 valid-auc:0.643838
[159] train-auc:0.79421 valid-auc:0.643799
[160] train-auc:0.794658 valid-auc:0.643908
[161] train-auc:0.795598 valid-auc:0.644001
[162] train-auc:0.796459 valid-auc:0.644341
[163] train-auc:0.797438 valid-auc:0.643406
[164] train-auc:0.797532 valid-auc:0.643418
[165] train-auc:0.79808 valid-auc:0.643112
[166] train-auc:0.798745 valid-auc:0.64285
[167] train-auc:0.799452 valid-auc:0.642474
[168] train-auc:0.799767 valid-auc:0.642185
[169] train-auc:0.800323 valid-auc:0.641992
[170] train-auc:0.801209 valid-auc:0.642384
[171] train-auc:0.801753 valid-auc:0.642261
[172] train-auc:0.802079 valid-auc:0.64265
[173] train-auc:0.802839 valid-auc:0.642558
[174] train-auc:0.803313 valid-auc:0.642898
[175] train-auc:0.803692 valid-auc:0.642653
[176] train-auc:0.803968 valid-auc:0.641972
[177] train-auc:0.804133 valid-auc:0.642493
[178] train-auc:0.805044 valid-auc:0.642464
[179] train-auc:0.806052 valid-auc:0.642652
[180] train-auc:0.806033 valid-auc:0.642538
[181] train-auc:0.806147 valid-auc:0.642438
[182] train-auc:0.806452 valid-auc:0.642521
[183] train-auc:0.807203 valid-auc:0.642529
[184] train-auc:0.807461 valid-auc:0.642625
[185] train-auc:0.807713 valid-auc:0.642596
[186] train-auc:0.80802 valid-auc:0.642318
[187] train-auc:0.808506 valid-auc:0.642539
[188] train-auc:0.809058 valid-auc:0.641993
[189] train-auc:0.809657 valid-auc:0.641709
Stopping. Best iteration:
[139] train-auc:0.776009 valid-auc:0.645539
[mlcrate] Finished training fold 3 - took 10s - running score 0.67846675
[mlcrate] Running fold 4, 15737 train samples, 2622 validation samples
[0] train-auc:0.578554 valid-auc:0.576108
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.58972 valid-auc:0.582128
[2] train-auc:0.58972 valid-auc:0.582128
[3] train-auc:0.58972 valid-auc:0.582128
[4] train-auc:0.58972 valid-auc:0.582128
[5] train-auc:0.592651 valid-auc:0.583252
[6] train-auc:0.592651 valid-auc:0.583252
[7] train-auc:0.592651 valid-auc:0.583236
[8] train-auc:0.593445 valid-auc:0.585122
[9] train-auc:0.593442 valid-auc:0.585134
[10] train-auc:0.593525 valid-auc:0.584973
[11] train-auc:0.593525 valid-auc:0.584973
[12] train-auc:0.593809 valid-auc:0.585245
[13] train-auc:0.593809 valid-auc:0.585245
[14] train-auc:0.593809 valid-auc:0.585245
[15] train-auc:0.593916 valid-auc:0.585306
[16] train-auc:0.593923 valid-auc:0.585291
[17] train-auc:0.593923 valid-auc:0.585291
[18] train-auc:0.593923 valid-auc:0.585291
[19] train-auc:0.594087 valid-auc:0.585419
[20] train-auc:0.595186 valid-auc:0.585829
[21] train-auc:0.595037 valid-auc:0.585194
[22] train-auc:0.650366 valid-auc:0.635599
[23] train-auc:0.650906 valid-auc:0.636147
[24] train-auc:0.651902 valid-auc:0.63606
[25] train-auc:0.652717 valid-auc:0.636335
[26] train-auc:0.652794 valid-auc:0.636464
[27] train-auc:0.660014 valid-auc:0.63732
[28] train-auc:0.659662 valid-auc:0.637025
[29] train-auc:0.662675 valid-auc:0.637933
[30] train-auc:0.663708 valid-auc:0.638384
[31] train-auc:0.665307 valid-auc:0.639946
[32] train-auc:0.665999 valid-auc:0.638425
[33] train-auc:0.666181 valid-auc:0.637669
[34] train-auc:0.667073 valid-auc:0.63773
[35] train-auc:0.667618 valid-auc:0.637777
[36] train-auc:0.668099 valid-auc:0.638397
[37] train-auc:0.66853 valid-auc:0.639054
[38] train-auc:0.668623 valid-auc:0.638722
[39] train-auc:0.670562 valid-auc:0.63797
[40] train-auc:0.671361 valid-auc:0.636076
[41] train-auc:0.671739 valid-auc:0.636994
[42] train-auc:0.672405 valid-auc:0.636623
[43] train-auc:0.674106 valid-auc:0.636222
[44] train-auc:0.67504 valid-auc:0.636914
[45] train-auc:0.676826 valid-auc:0.639284
[46] train-auc:0.677703 valid-auc:0.638951
[47] train-auc:0.678844 valid-auc:0.639776
[48] train-auc:0.679858 valid-auc:0.64057
[49] train-auc:0.680756 valid-auc:0.641718
[50] train-auc:0.682523 valid-auc:0.640723
[51] train-auc:0.68284 valid-auc:0.640051
[52] train-auc:0.683092 valid-auc:0.640265
[53] train-auc:0.683597 valid-auc:0.64046
[54] train-auc:0.683961 valid-auc:0.640142
[55] train-auc:0.685027 valid-auc:0.640735
[56] train-auc:0.685766 valid-auc:0.641034
[57] train-auc:0.689085 valid-auc:0.64267
[58] train-auc:0.689345 valid-auc:0.642529
[59] train-auc:0.689814 valid-auc:0.643329
[60] train-auc:0.690199 valid-auc:0.643717
[61] train-auc:0.691065 valid-auc:0.64414
[62] train-auc:0.693272 valid-auc:0.643959
[63] train-auc:0.693654 valid-auc:0.643736
[64] train-auc:0.693863 valid-auc:0.641776
[65] train-auc:0.694161 valid-auc:0.641561
[66] train-auc:0.694491 valid-auc:0.641142
[67] train-auc:0.694798 valid-auc:0.642643
[68] train-auc:0.696644 valid-auc:0.642792
[69] train-auc:0.699365 valid-auc:0.643529
[70] train-auc:0.701946 valid-auc:0.647175
[71] train-auc:0.702346 valid-auc:0.647766
[72] train-auc:0.703149 valid-auc:0.647658
[73] train-auc:0.70421 valid-auc:0.647961
[74] train-auc:0.705236 valid-auc:0.648444
[75] train-auc:0.706843 valid-auc:0.649148
[76] train-auc:0.707773 valid-auc:0.649924
[77] train-auc:0.709872 valid-auc:0.651066
[78] train-auc:0.710234 valid-auc:0.650873
[79] train-auc:0.711686 valid-auc:0.65026
[80] train-auc:0.713741 valid-auc:0.650071
[81] train-auc:0.71461 valid-auc:0.650986
[82] train-auc:0.71474 valid-auc:0.651134
[83] train-auc:0.715225 valid-auc:0.650869
[84] train-auc:0.715948 valid-auc:0.650779
[85] train-auc:0.717305 valid-auc:0.651597
[86] train-auc:0.71901 valid-auc:0.651446
[87] train-auc:0.719731 valid-auc:0.652089
[88] train-auc:0.721268 valid-auc:0.65304
[89] train-auc:0.721851 valid-auc:0.653513
[90] train-auc:0.723567 valid-auc:0.655273
[91] train-auc:0.725053 valid-auc:0.654749
[92] train-auc:0.725906 valid-auc:0.654592
[93] train-auc:0.726737 valid-auc:0.65598
[94] train-auc:0.728206 valid-auc:0.656603
[95] train-auc:0.728981 valid-auc:0.656164
[96] train-auc:0.729709 valid-auc:0.656389
[97] train-auc:0.731482 valid-auc:0.657968
[98] train-auc:0.732759 valid-auc:0.65835
[99] train-auc:0.733846 valid-auc:0.658252
[100] train-auc:0.734591 valid-auc:0.658586
[101] train-auc:0.735616 valid-auc:0.65892
[102] train-auc:0.737257 valid-auc:0.658852
[103] train-auc:0.738887 valid-auc:0.658394
[104] train-auc:0.74054 valid-auc:0.657565
[105] train-auc:0.741504 valid-auc:0.657256
[106] train-auc:0.741982 valid-auc:0.656677
[107] train-auc:0.743337 valid-auc:0.656797
[108] train-auc:0.74485 valid-auc:0.657462
[109] train-auc:0.746762 valid-auc:0.657559
[110] train-auc:0.747322 valid-auc:0.657748
[111] train-auc:0.748216 valid-auc:0.657757
[112] train-auc:0.749619 valid-auc:0.657936
[113] train-auc:0.750594 valid-auc:0.658457
[114] train-auc:0.751253 valid-auc:0.65862
[115] train-auc:0.752291 valid-auc:0.659483
[116] train-auc:0.75278 valid-auc:0.659207
[117] train-auc:0.754562 valid-auc:0.659543
[118] train-auc:0.755641 valid-auc:0.659888
[119] train-auc:0.756093 valid-auc:0.660111
[120] train-auc:0.757043 valid-auc:0.660193
[121] train-auc:0.757586 valid-auc:0.660445
[122] train-auc:0.758622 valid-auc:0.660535
[123] train-auc:0.759251 valid-auc:0.660482
[124] train-auc:0.760335 valid-auc:0.660111
[125] train-auc:0.761475 valid-auc:0.660256
[126] train-auc:0.762494 valid-auc:0.659836
[127] train-auc:0.762689 valid-auc:0.659626
[128] train-auc:0.764308 valid-auc:0.659474
[129] train-auc:0.76467 valid-auc:0.659514
[130] train-auc:0.765236 valid-auc:0.659333
[131] train-auc:0.765502 valid-auc:0.659304
[132] train-auc:0.766512 valid-auc:0.659655
[133] train-auc:0.767084 valid-auc:0.659605
[134] train-auc:0.767599 valid-auc:0.659682
[135] train-auc:0.767972 valid-auc:0.659794
[136] train-auc:0.768604 valid-auc:0.660326
[137] train-auc:0.769244 valid-auc:0.659928
[138] train-auc:0.769601 valid-auc:0.65984
[139] train-auc:0.770113 valid-auc:0.659724
[140] train-auc:0.770973 valid-auc:0.659647
[141] train-auc:0.771906 valid-auc:0.660488
[142] train-auc:0.772775 valid-auc:0.66011
[143] train-auc:0.773494 valid-auc:0.660881
[144] train-auc:0.774191 valid-auc:0.661098
[145] train-auc:0.774226 valid-auc:0.661196
[146] train-auc:0.774811 valid-auc:0.661104
[147] train-auc:0.775411 valid-auc:0.661427
[148] train-auc:0.776035 valid-auc:0.661498
[149] train-auc:0.776404 valid-auc:0.66124
[150] train-auc:0.777272 valid-auc:0.661404
[151] train-auc:0.777636 valid-auc:0.661312
[152] train-auc:0.778436 valid-auc:0.660688
[153] train-auc:0.779002 valid-auc:0.660582
[154] train-auc:0.779995 valid-auc:0.660483
[155] train-auc:0.781248 valid-auc:0.660368
[156] train-auc:0.782357 valid-auc:0.661167
[157] train-auc:0.783454 valid-auc:0.660763
[158] train-auc:0.783981 valid-auc:0.660812
[159] train-auc:0.784538 valid-auc:0.66088
[160] train-auc:0.785132 valid-auc:0.66076
[161] train-auc:0.786538 valid-auc:0.660657
[162] train-auc:0.786773 valid-auc:0.660472
[163] train-auc:0.78687 valid-auc:0.660118
[164] train-auc:0.787236 valid-auc:0.660394
[165] train-auc:0.787236 valid-auc:0.660394
[166] train-auc:0.787669 valid-auc:0.660529
[167] train-auc:0.788661 valid-auc:0.661368
[168] train-auc:0.788965 valid-auc:0.661334
[169] train-auc:0.79001 valid-auc:0.660708
[170] train-auc:0.79001 valid-auc:0.660708
[171] train-auc:0.790304 valid-auc:0.661091
[172] train-auc:0.790334 valid-auc:0.661137
[173] train-auc:0.790714 valid-auc:0.661127
[174] train-auc:0.791223 valid-auc:0.661532
[175] train-auc:0.791673 valid-auc:0.66128
[176] train-auc:0.791715 valid-auc:0.661551
[177] train-auc:0.792681 valid-auc:0.662092
[178] train-auc:0.793839 valid-auc:0.661972
[179] train-auc:0.794287 valid-auc:0.662096
[180] train-auc:0.794809 valid-auc:0.662224
[181] train-auc:0.795709 valid-auc:0.662953
[182] train-auc:0.795816 valid-auc:0.663217
[183] train-auc:0.796172 valid-auc:0.663046
[184] train-auc:0.796487 valid-auc:0.663235
[185] train-auc:0.796678 valid-auc:0.663205
[186] train-auc:0.797142 valid-auc:0.662483
[187] train-auc:0.797199 valid-auc:0.662199
[188] train-auc:0.797473 valid-auc:0.661875
[189] train-auc:0.797729 valid-auc:0.661935
[190] train-auc:0.798149 valid-auc:0.661757
[191] train-auc:0.798651 valid-auc:0.662139
[192] train-auc:0.799317 valid-auc:0.661502
[193] train-auc:0.799504 valid-auc:0.66155
[194] train-auc:0.79983 valid-auc:0.661478
[195] train-auc:0.800811 valid-auc:0.661374
[196] train-auc:0.801222 valid-auc:0.661109
[197] train-auc:0.80213 valid-auc:0.660651
[198] train-auc:0.80245 valid-auc:0.661087
[199] train-auc:0.802846 valid-auc:0.660991
[200] train-auc:0.802863 valid-auc:0.661048
[201] train-auc:0.803295 valid-auc:0.661045
[202] train-auc:0.804328 valid-auc:0.660546
[203] train-auc:0.804465 valid-auc:0.66032
[204] train-auc:0.804911 valid-auc:0.66053
[205] train-auc:0.805338 valid-auc:0.66096
[206] train-auc:0.805992 valid-auc:0.660923
[207] train-auc:0.807065 valid-auc:0.660212
[208] train-auc:0.807594 valid-auc:0.660078
[209] train-auc:0.808067 valid-auc:0.660372
[210] train-auc:0.808526 valid-auc:0.660293
[211] train-auc:0.80881 valid-auc:0.660392
[212] train-auc:0.809097 valid-auc:0.660604
[213] train-auc:0.809424 valid-auc:0.660687
[214] train-auc:0.810009 valid-auc:0.660608
[215] train-auc:0.810009 valid-auc:0.660608
[216] train-auc:0.810366 valid-auc:0.660949
[217] train-auc:0.810508 valid-auc:0.661036
[218] train-auc:0.811139 valid-auc:0.661175
[219] train-auc:0.811342 valid-auc:0.660986
[220] train-auc:0.811797 valid-auc:0.661419
[221] train-auc:0.812351 valid-auc:0.661394
[222] train-auc:0.812781 valid-auc:0.661705
[223] train-auc:0.813149 valid-auc:0.662228
[224] train-auc:0.813401 valid-auc:0.662405
[225] train-auc:0.813632 valid-auc:0.662195
[226] train-auc:0.814393 valid-auc:0.662323
[227] train-auc:0.815249 valid-auc:0.662256
[228] train-auc:0.81585 valid-auc:0.662437
[229] train-auc:0.816021 valid-auc:0.662038
[230] train-auc:0.816823 valid-auc:0.661935
[231] train-auc:0.81698 valid-auc:0.662377
[232] train-auc:0.817678 valid-auc:0.661852
[233] train-auc:0.818488 valid-auc:0.661864
[234] train-auc:0.818939 valid-auc:0.661916
Stopping. Best iteration:
[184] train-auc:0.796487 valid-auc:0.663235
[mlcrate] Finished training fold 4 - took 12s - running score 0.6754203999999999
[mlcrate] Running fold 5, 15737 train samples, 2622 validation samples
[0] train-auc:0.5 valid-auc:0.5
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.573992 valid-auc:0.562536
[2] train-auc:0.575218 valid-auc:0.566533
[3] train-auc:0.578604 valid-auc:0.577277
[4] train-auc:0.578604 valid-auc:0.577277
[5] train-auc:0.578604 valid-auc:0.577277
[6] train-auc:0.579056 valid-auc:0.576955
[7] train-auc:0.579056 valid-auc:0.576955
[8] train-auc:0.582164 valid-auc:0.581819
[9] train-auc:0.589554 valid-auc:0.592599
[10] train-auc:0.589809 valid-auc:0.592545
[11] train-auc:0.589865 valid-auc:0.592485
[12] train-auc:0.589883 valid-auc:0.592457
[13] train-auc:0.589883 valid-auc:0.592457
[14] train-auc:0.58988 valid-auc:0.592448
[15] train-auc:0.590229 valid-auc:0.592632
[16] train-auc:0.590229 valid-auc:0.592632
[17] train-auc:0.590229 valid-auc:0.592632
[18] train-auc:0.590229 valid-auc:0.592632
[19] train-auc:0.590213 valid-auc:0.592632
[20] train-auc:0.611001 valid-auc:0.608715
[21] train-auc:0.617944 valid-auc:0.612498
[22] train-auc:0.653867 valid-auc:0.648773
[23] train-auc:0.655393 valid-auc:0.65029
[24] train-auc:0.658499 valid-auc:0.651128
[25] train-auc:0.660191 valid-auc:0.647199
[26] train-auc:0.660557 valid-auc:0.646818
[27] train-auc:0.660293 valid-auc:0.647818
[28] train-auc:0.661015 valid-auc:0.646493
[29] train-auc:0.66245 valid-auc:0.647064
[30] train-auc:0.662697 valid-auc:0.646965
[31] train-auc:0.662773 valid-auc:0.646985
[32] train-auc:0.663685 valid-auc:0.647517
[33] train-auc:0.66388 valid-auc:0.648026
[34] train-auc:0.663883 valid-auc:0.647918
[35] train-auc:0.663632 valid-auc:0.647984
[36] train-auc:0.664254 valid-auc:0.648358
[37] train-auc:0.664748 valid-auc:0.648556
[38] train-auc:0.666942 valid-auc:0.646737
[39] train-auc:0.667253 valid-auc:0.646202
[40] train-auc:0.667389 valid-auc:0.646186
[41] train-auc:0.667407 valid-auc:0.646168
[42] train-auc:0.668948 valid-auc:0.646022
[43] train-auc:0.669864 valid-auc:0.646842
[44] train-auc:0.670168 valid-auc:0.646749
[45] train-auc:0.670693 valid-auc:0.646223
[46] train-auc:0.672517 valid-auc:0.647712
[47] train-auc:0.672889 valid-auc:0.647664
[48] train-auc:0.673612 valid-auc:0.647906
[49] train-auc:0.674055 valid-auc:0.648188
[50] train-auc:0.674349 valid-auc:0.649006
[51] train-auc:0.674537 valid-auc:0.649043
[52] train-auc:0.675882 valid-auc:0.648421
[53] train-auc:0.676631 valid-auc:0.648194
[54] train-auc:0.677733 valid-auc:0.648462
[55] train-auc:0.678782 valid-auc:0.649172
[56] train-auc:0.679036 valid-auc:0.64958
[57] train-auc:0.684922 valid-auc:0.659261
[58] train-auc:0.685249 valid-auc:0.659076
[59] train-auc:0.685448 valid-auc:0.658995
[60] train-auc:0.686017 valid-auc:0.660443
[61] train-auc:0.686222 valid-auc:0.659809
[62] train-auc:0.687084 valid-auc:0.660293
[63] train-auc:0.689337 valid-auc:0.659377
[64] train-auc:0.690008 valid-auc:0.659359
[65] train-auc:0.689896 valid-auc:0.659135
[66] train-auc:0.691478 valid-auc:0.661038
[67] train-auc:0.694442 valid-auc:0.66042
[68] train-auc:0.695312 valid-auc:0.661681
[69] train-auc:0.695581 valid-auc:0.662129
[70] train-auc:0.696703 valid-auc:0.663455
[71] train-auc:0.698382 valid-auc:0.663708
[72] train-auc:0.701632 valid-auc:0.664043
[73] train-auc:0.702694 valid-auc:0.664469
[74] train-auc:0.703351 valid-auc:0.665628
[75] train-auc:0.706543 valid-auc:0.66684
[76] train-auc:0.708204 valid-auc:0.666831
[77] train-auc:0.709139 valid-auc:0.668131
[78] train-auc:0.710918 valid-auc:0.668031
[79] train-auc:0.711473 valid-auc:0.668733
[80] train-auc:0.711838 valid-auc:0.668938
[81] train-auc:0.711779 valid-auc:0.668551
[82] train-auc:0.712933 valid-auc:0.668546
[83] train-auc:0.713571 valid-auc:0.668088
[84] train-auc:0.71518 valid-auc:0.668421
[85] train-auc:0.716481 valid-auc:0.66815
[86] train-auc:0.717897 valid-auc:0.667581
[87] train-auc:0.719059 valid-auc:0.668428
[88] train-auc:0.720359 valid-auc:0.669014
[89] train-auc:0.721902 valid-auc:0.668579
[90] train-auc:0.722828 valid-auc:0.66889
[91] train-auc:0.725128 valid-auc:0.669237
[92] train-auc:0.727184 valid-auc:0.668515
[93] train-auc:0.729192 valid-auc:0.668591
[94] train-auc:0.729068 valid-auc:0.668715
[95] train-auc:0.730273 valid-auc:0.668558
[96] train-auc:0.731968 valid-auc:0.668808
[97] train-auc:0.733166 valid-auc:0.668515
[98] train-auc:0.735354 valid-auc:0.670285
[99] train-auc:0.736002 valid-auc:0.670285
[100] train-auc:0.73734 valid-auc:0.670498
[101] train-auc:0.73852 valid-auc:0.670645
[102] train-auc:0.739801 valid-auc:0.670299
[103] train-auc:0.740464 valid-auc:0.671126
[104] train-auc:0.740464 valid-auc:0.670931
[105] train-auc:0.741817 valid-auc:0.671388
[106] train-auc:0.742827 valid-auc:0.671514
[107] train-auc:0.745 valid-auc:0.670864
[108] train-auc:0.746046 valid-auc:0.670678
[109] train-auc:0.746741 valid-auc:0.670151
[110] train-auc:0.74722 valid-auc:0.670625
[111] train-auc:0.748149 valid-auc:0.670303
[112] train-auc:0.749311 valid-auc:0.671489
[113] train-auc:0.750769 valid-auc:0.671554
[114] train-auc:0.751917 valid-auc:0.671527
[115] train-auc:0.752676 valid-auc:0.671535
[116] train-auc:0.753755 valid-auc:0.670596
[117] train-auc:0.754714 valid-auc:0.671094
[118] train-auc:0.756025 valid-auc:0.671242
[119] train-auc:0.757086 valid-auc:0.671542
[120] train-auc:0.757433 valid-auc:0.671701
[121] train-auc:0.758303 valid-auc:0.671308
[122] train-auc:0.759304 valid-auc:0.67058
[123] train-auc:0.760033 valid-auc:0.670174
[124] train-auc:0.760504 valid-auc:0.669926
[125] train-auc:0.760762 valid-auc:0.669781
[126] train-auc:0.761764 valid-auc:0.670263
[127] train-auc:0.762536 valid-auc:0.670087
[128] train-auc:0.763507 valid-auc:0.670391
[129] train-auc:0.764945 valid-auc:0.670518
[130] train-auc:0.76627 valid-auc:0.671069
[131] train-auc:0.766761 valid-auc:0.671052
[132] train-auc:0.767652 valid-auc:0.670979
[133] train-auc:0.768054 valid-auc:0.671215
[134] train-auc:0.768605 valid-auc:0.670627
[135] train-auc:0.769722 valid-auc:0.669737
[136] train-auc:0.770747 valid-auc:0.669544
[137] train-auc:0.771162 valid-auc:0.669595
[138] train-auc:0.771693 valid-auc:0.669682
[139] train-auc:0.772281 valid-auc:0.668962
[140] train-auc:0.772926 valid-auc:0.669239
[141] train-auc:0.773144 valid-auc:0.669546
[142] train-auc:0.773535 valid-auc:0.668944
[143] train-auc:0.774373 valid-auc:0.668817
[144] train-auc:0.774901 valid-auc:0.668849
[145] train-auc:0.776236 valid-auc:0.669093
[146] train-auc:0.777404 valid-auc:0.669065
[147] train-auc:0.778287 valid-auc:0.669313
[148] train-auc:0.778482 valid-auc:0.669287
[149] train-auc:0.779305 valid-auc:0.669055
[150] train-auc:0.779643 valid-auc:0.669092
[151] train-auc:0.779643 valid-auc:0.669092
[152] train-auc:0.780175 valid-auc:0.669051
[153] train-auc:0.780699 valid-auc:0.669553
[154] train-auc:0.781741 valid-auc:0.670767
[155] train-auc:0.781849 valid-auc:0.670603
[156] train-auc:0.782221 valid-auc:0.670364
[157] train-auc:0.78253 valid-auc:0.670383
[158] train-auc:0.782735 valid-auc:0.670201
[159] train-auc:0.78277 valid-auc:0.670139
[160] train-auc:0.783575 valid-auc:0.669595
[161] train-auc:0.78456 valid-auc:0.669648
[162] train-auc:0.784689 valid-auc:0.669685
[163] train-auc:0.784831 valid-auc:0.669309
[164] train-auc:0.785492 valid-auc:0.66978
[165] train-auc:0.785831 valid-auc:0.670582
[166] train-auc:0.786168 valid-auc:0.669847
[167] train-auc:0.786459 valid-auc:0.669975
[168] train-auc:0.786975 valid-auc:0.670334
[169] train-auc:0.78758 valid-auc:0.669893
[170] train-auc:0.787765 valid-auc:0.669568
Stopping. Best iteration:
[120] train-auc:0.757433 valid-auc:0.671701
[mlcrate] Finished training fold 5 - took 9s - running score 0.6748004999999999
[mlcrate] Running fold 6, 15737 train samples, 2622 validation samples
[0] train-auc:0.588844 valid-auc:0.576753
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.590291 valid-auc:0.578684
[2] train-auc:0.59053 valid-auc:0.578684
[3] train-auc:0.59053 valid-auc:0.578684
[4] train-auc:0.59053 valid-auc:0.578684
[5] train-auc:0.590513 valid-auc:0.578745
[6] train-auc:0.590513 valid-auc:0.578745
[7] train-auc:0.590513 valid-auc:0.578745
[8] train-auc:0.591713 valid-auc:0.578938
[9] train-auc:0.591713 valid-auc:0.578938
[10] train-auc:0.592621 valid-auc:0.57733
[11] train-auc:0.592947 valid-auc:0.57742
[12] train-auc:0.592947 valid-auc:0.57742
[13] train-auc:0.592936 valid-auc:0.577423
[14] train-auc:0.59336 valid-auc:0.576731
[15] train-auc:0.593337 valid-auc:0.576756
[16] train-auc:0.593352 valid-auc:0.576798
[17] train-auc:0.593352 valid-auc:0.576798
[18] train-auc:0.593352 valid-auc:0.576798
[19] train-auc:0.593352 valid-auc:0.576798
[20] train-auc:0.593352 valid-auc:0.576798
[21] train-auc:0.593385 valid-auc:0.576741
[22] train-auc:0.599599 valid-auc:0.586543
[23] train-auc:0.650572 valid-auc:0.645264
[24] train-auc:0.651839 valid-auc:0.646639
[25] train-auc:0.651718 valid-auc:0.64654
[26] train-auc:0.651677 valid-auc:0.644157
[27] train-auc:0.652953 valid-auc:0.645029
[28] train-auc:0.653055 valid-auc:0.645507
[29] train-auc:0.657204 valid-auc:0.642198
[30] train-auc:0.65726 valid-auc:0.642894
[31] train-auc:0.659812 valid-auc:0.645295
[32] train-auc:0.660125 valid-auc:0.646043
[33] train-auc:0.660683 valid-auc:0.646232
[34] train-auc:0.661127 valid-auc:0.647015
[35] train-auc:0.662546 valid-auc:0.647146
[36] train-auc:0.662714 valid-auc:0.647794
[37] train-auc:0.662703 valid-auc:0.648215
[38] train-auc:0.662746 valid-auc:0.648295
[39] train-auc:0.664757 valid-auc:0.650318
[40] train-auc:0.665982 valid-auc:0.651223
[41] train-auc:0.666909 valid-auc:0.651693
[42] train-auc:0.666697 valid-auc:0.652355
[43] train-auc:0.667377 valid-auc:0.652205
[44] train-auc:0.669487 valid-auc:0.650859
[45] train-auc:0.670016 valid-auc:0.650815
[46] train-auc:0.670699 valid-auc:0.650541
[47] train-auc:0.673607 valid-auc:0.654166
[48] train-auc:0.674813 valid-auc:0.654593
[49] train-auc:0.675855 valid-auc:0.653518
[50] train-auc:0.67625 valid-auc:0.654052
[51] train-auc:0.680162 valid-auc:0.65689
[52] train-auc:0.680595 valid-auc:0.657688
[53] train-auc:0.680781 valid-auc:0.658079
[54] train-auc:0.681356 valid-auc:0.658692
[55] train-auc:0.681787 valid-auc:0.659636
[56] train-auc:0.682547 valid-auc:0.659574
[57] train-auc:0.684104 valid-auc:0.658264
[58] train-auc:0.684564 valid-auc:0.659582
[59] train-auc:0.685702 valid-auc:0.66113
[60] train-auc:0.686962 valid-auc:0.661541
[61] train-auc:0.688415 valid-auc:0.662134
[62] train-auc:0.689016 valid-auc:0.661812
[63] train-auc:0.690023 valid-auc:0.662648
[64] train-auc:0.690295 valid-auc:0.663292
[65] train-auc:0.694537 valid-auc:0.66351
[66] train-auc:0.697061 valid-auc:0.667468
[67] train-auc:0.697653 valid-auc:0.666903
[68] train-auc:0.698527 valid-auc:0.667214
[69] train-auc:0.698916 valid-auc:0.666898
[70] train-auc:0.699935 valid-auc:0.666829
[71] train-auc:0.700832 valid-auc:0.667038
[72] train-auc:0.701199 valid-auc:0.6675
[73] train-auc:0.702365 valid-auc:0.666659
[74] train-auc:0.703263 valid-auc:0.666565
[75] train-auc:0.705657 valid-auc:0.666432
[76] train-auc:0.708151 valid-auc:0.667774
[77] train-auc:0.709786 valid-auc:0.6688
[78] train-auc:0.710425 valid-auc:0.6684
[79] train-auc:0.711636 valid-auc:0.668359
[80] train-auc:0.712998 valid-auc:0.668687
[81] train-auc:0.71319 valid-auc:0.668078
[82] train-auc:0.7147 valid-auc:0.668055
[83] train-auc:0.715222 valid-auc:0.668271
[84] train-auc:0.71647 valid-auc:0.668654
[85] train-auc:0.71705 valid-auc:0.668438
[86] train-auc:0.720492 valid-auc:0.668934
[87] train-auc:0.722495 valid-auc:0.668593
[88] train-auc:0.723986 valid-auc:0.669398
[89] train-auc:0.724872 valid-auc:0.669198
[90] train-auc:0.725471 valid-auc:0.669055
[91] train-auc:0.726861 valid-auc:0.669222
[92] train-auc:0.728274 valid-auc:0.669219
[93] train-auc:0.729392 valid-auc:0.668924
[94] train-auc:0.729755 valid-auc:0.669694
[95] train-auc:0.7301 valid-auc:0.670262
[96] train-auc:0.731624 valid-auc:0.66989
[97] train-auc:0.73226 valid-auc:0.669704
[98] train-auc:0.73301 valid-auc:0.670523
[99] train-auc:0.734441 valid-auc:0.671057
[100] train-auc:0.735147 valid-auc:0.670824
[101] train-auc:0.735505 valid-auc:0.670802
[102] train-auc:0.735836 valid-auc:0.671033
[103] train-auc:0.737812 valid-auc:0.672015
[104] train-auc:0.739671 valid-auc:0.672506
[105] train-auc:0.740482 valid-auc:0.672177
[106] train-auc:0.742494 valid-auc:0.672376
[107] train-auc:0.743183 valid-auc:0.673418
[108] train-auc:0.744373 valid-auc:0.673316
[109] train-auc:0.74536 valid-auc:0.672711
[110] train-auc:0.746313 valid-auc:0.67169
[111] train-auc:0.747061 valid-auc:0.671674
[112] train-auc:0.748761 valid-auc:0.6712
[113] train-auc:0.749531 valid-auc:0.671098
[114] train-auc:0.751105 valid-auc:0.671871
[115] train-auc:0.751763 valid-auc:0.672114
[116] train-auc:0.75324 valid-auc:0.672161
[117] train-auc:0.753725 valid-auc:0.672728
[118] train-auc:0.755265 valid-auc:0.673285
[119] train-auc:0.755936 valid-auc:0.673188
[120] train-auc:0.75645 valid-auc:0.673046
[121] train-auc:0.756616 valid-auc:0.673329
[122] train-auc:0.757284 valid-auc:0.673304
[123] train-auc:0.758072 valid-auc:0.674228
[124] train-auc:0.759116 valid-auc:0.673843
[125] train-auc:0.761376 valid-auc:0.673873
[126] train-auc:0.761823 valid-auc:0.67369
[127] train-auc:0.762774 valid-auc:0.672934
[128] train-auc:0.763254 valid-auc:0.672765
[129] train-auc:0.764045 valid-auc:0.67258
[130] train-auc:0.764916 valid-auc:0.672735
[131] train-auc:0.765288 valid-auc:0.672774
[132] train-auc:0.766328 valid-auc:0.673051
[133] train-auc:0.767251 valid-auc:0.673565
[134] train-auc:0.767515 valid-auc:0.673701
[135] train-auc:0.768305 valid-auc:0.673441
[136] train-auc:0.768598 valid-auc:0.673348
[137] train-auc:0.770205 valid-auc:0.67228
[138] train-auc:0.770575 valid-auc:0.671955
[139] train-auc:0.771698 valid-auc:0.671574
[140] train-auc:0.772552 valid-auc:0.671494
[141] train-auc:0.773177 valid-auc:0.671578
[142] train-auc:0.774634 valid-auc:0.671776
[143] train-auc:0.775467 valid-auc:0.671285
[144] train-auc:0.776359 valid-auc:0.671394
[145] train-auc:0.776608 valid-auc:0.671193
[146] train-auc:0.77708 valid-auc:0.671643
[147] train-auc:0.777585 valid-auc:0.67219
[148] train-auc:0.777962 valid-auc:0.67232
[149] train-auc:0.778213 valid-auc:0.67246
[150] train-auc:0.7789 valid-auc:0.67232
[151] train-auc:0.77925 valid-auc:0.672751
[152] train-auc:0.779777 valid-auc:0.672924
[153] train-auc:0.780014 valid-auc:0.67267
[154] train-auc:0.780155 valid-auc:0.672635
[155] train-auc:0.780991 valid-auc:0.672716
[156] train-auc:0.781856 valid-auc:0.672727
[157] train-auc:0.783054 valid-auc:0.673208
[158] train-auc:0.783597 valid-auc:0.673254
[159] train-auc:0.784726 valid-auc:0.673841
[160] train-auc:0.784988 valid-auc:0.673973
[161] train-auc:0.784988 valid-auc:0.673973
[162] train-auc:0.785711 valid-auc:0.673705
[163] train-auc:0.786167 valid-auc:0.673988
[164] train-auc:0.786328 valid-auc:0.674137
[165] train-auc:0.786914 valid-auc:0.674304
[166] train-auc:0.78722 valid-auc:0.674064
[167] train-auc:0.787445 valid-auc:0.674268
[168] train-auc:0.788025 valid-auc:0.674367
[169] train-auc:0.788059 valid-auc:0.674493
[170] train-auc:0.788534 valid-auc:0.674351
[171] train-auc:0.788625 valid-auc:0.674515
[172] train-auc:0.78866 valid-auc:0.674373
[173] train-auc:0.788955 valid-auc:0.674569
[174] train-auc:0.789358 valid-auc:0.674695
[175] train-auc:0.789688 valid-auc:0.674641
[176] train-auc:0.790137 valid-auc:0.674359
[177] train-auc:0.790774 valid-auc:0.674607
[178] train-auc:0.791265 valid-auc:0.674195
[179] train-auc:0.792048 valid-auc:0.674153
[180] train-auc:0.792857 valid-auc:0.673861
[181] train-auc:0.792957 valid-auc:0.673899
[182] train-auc:0.79341 valid-auc:0.673635
[183] train-auc:0.794358 valid-auc:0.673344
[184] train-auc:0.794696 valid-auc:0.673103
[185] train-auc:0.794849 valid-auc:0.672857
[186] train-auc:0.795084 valid-auc:0.672736
[187] train-auc:0.795395 valid-auc:0.672907
[188] train-auc:0.796057 valid-auc:0.672983
[189] train-auc:0.797045 valid-auc:0.672822
[190] train-auc:0.797234 valid-auc:0.672595
[191] train-auc:0.797848 valid-auc:0.672182
[192] train-auc:0.798177 valid-auc:0.672254
[193] train-auc:0.798736 valid-auc:0.672406
[194] train-auc:0.798804 valid-auc:0.672627
[195] train-auc:0.799377 valid-auc:0.672825
[196] train-auc:0.799658 valid-auc:0.672914
[197] train-auc:0.799658 valid-auc:0.672914
[198] train-auc:0.8 valid-auc:0.672615
[199] train-auc:0.800275 valid-auc:0.67251
[200] train-auc:0.80064 valid-auc:0.672739
[201] train-auc:0.800851 valid-auc:0.672212
[202] train-auc:0.802049 valid-auc:0.672129
[203] train-auc:0.802411 valid-auc:0.672129
[204] train-auc:0.802504 valid-auc:0.6721
[205] train-auc:0.802915 valid-auc:0.671583
[206] train-auc:0.803501 valid-auc:0.671944
[207] train-auc:0.803951 valid-auc:0.671823
[208] train-auc:0.805028 valid-auc:0.671915
[209] train-auc:0.805278 valid-auc:0.671923
[210] train-auc:0.805278 valid-auc:0.671923
[211] train-auc:0.80587 valid-auc:0.6717
[212] train-auc:0.806136 valid-auc:0.6716
[213] train-auc:0.80629 valid-auc:0.671172
[214] train-auc:0.807284 valid-auc:0.670428
[215] train-auc:0.807565 valid-auc:0.670326
[216] train-auc:0.808305 valid-auc:0.670339
[217] train-auc:0.808641 valid-auc:0.669823
[218] train-auc:0.808849 valid-auc:0.669915
[219] train-auc:0.809295 valid-auc:0.669754
[220] train-auc:0.809323 valid-auc:0.669796
[221] train-auc:0.809667 valid-auc:0.669819
[222] train-auc:0.810262 valid-auc:0.669704
[223] train-auc:0.810759 valid-auc:0.669639
[224] train-auc:0.811151 valid-auc:0.66984
Stopping. Best iteration:
[174] train-auc:0.789358 valid-auc:0.674695
[mlcrate] Finished training fold 6 - took 12s - running score 0.6747854285714284
[mlcrate] Finished training 7 XGBoost models, took 1m09s
In [11]:
xgb.plot_importance(model_xgb[0],max_num_features=12)
Out[11]:
<matplotlib.axes._subplots.AxesSubplot at 0x21c4d6aa2b0>
In [133]:
np.save(f'{PATH}\\AV_Stud_2\\train_67.npy', X_stack_train)
np.save(f'{PATH}\\AV_Stud_2\\test_67.npy', X_stack_test)
np.save(f'{PATH}\\AV_Stud_2\\target.npy', target)
In [7]:
X_stack_train = np.load(f'{PATH}\\AV_Stud_2\\train_67.npy')
X_stack_test = np.load(f'{PATH}\\AV_Stud_2\\test_67.npy')
target = np.load(f'{PATH}\\AV_Stud_2\\target.npy')
In [20]:
clf_ada = AdaBoostClassifier(n_estimators=100, learning_rate= 0.05)
In [21]:
clf_ada.fit(X_stack_train, target)
Out[21]:
AdaBoostClassifier(algorithm='SAMME.R', base_estimator=None,
learning_rate=0.05, n_estimators=100, random_state=None)
In [51]:
preds = clf_ada.predict_proba(X_stack_test)[:, 1]
In [79]:
submit = make_submission(p_test)
submit.to_csv(f'{PATH}\\AV_Stud_2\\stacked_sklearn_showdown.csv', index=False)
submit.head(2)
Out[79]:
enrollee_id
target
0
16548
0.219328
1
12036
0.026984
In [53]:
stack_test = pd.DataFrame()
stack_train = pd.DataFrame()
log_cols=["Classifier", "Accuracy"]
log = pd.DataFrame(columns=log_cols)
In [54]:
def train_k_fold(x_train, y_train, model=None, x_test=None, folds=7, stratify=None, random_state=1337):
assert model is not None, "model can't be none, Please pass your model."
if hasattr(x_train, 'columns'):
columns = x_train.columns.values
columns_exists = True
else:
columns = np.arange(x_train.shape[1])
columns_exists = False
x_train = np.asarray(x_train)
y_train = np.array(y_train)
if x_test is not None:
if columns_exists:
try:
x_test = x_test[columns]
except Exception as e:
print('x_test columns doesn\'t match x_train columns.')
raise e
x_test = np.asarray(x_test)
assert x_train.shape[1] == x_test.shape[1], "x_train and x_test have different numbers of features."
print('Training {} {}models on training set {} {}'.format(folds, 'stratified ' if stratify is not None else '',
x_train.shape, 'with test set {}'.format(x_test.shape) if x_test is not None else 'without a test set'))
if stratify is not None:
kf = StratifiedKFold(n_splits=folds, shuffle=True, random_state=random_state)
splits = kf.split(x_train, stratify)
else:
kf = KFold(n_splits=folds, shuffle=True, random_state=4242)
splits = kf.split(x_train)
p_train = np.zeros_like(y_train, dtype=np.float32)
ps_test = []
models = []
scores = []
fold_i = 0
for train_kf, valid_kf in splits:
print('Running fold {}, {} train samples, {} validation samples'.format(fold_i, len(train_kf), len(valid_kf)))
d_train, label_train = x_train[train_kf], y_train[train_kf]
d_valid, label_valid = x_train[valid_kf], y_train[valid_kf]
mdl = model.fit(d_train,label_train)
scores.append(mdl.score(d_valid, label_valid))
print('Finished training fold {} - running score {} '.format(fold_i, np.mean(scores)))
# Get predictions from the model
if hasattr(mdl,'predict_proba'):
#print('Using model.predict_proba')
p_valid = mdl.predict_proba(d_valid)[:,1]
if x_test is not None:
p_test = mdl.predict_proba(x_test)[:,1]
else:
#print('Using model.predict')
p_valid = mdl.predict(d_valid)
if x_test is not None:
p_test = mdl.predict(x_test)
p_train[valid_kf] = p_valid
ps_test.append(p_test)
models.append(mdl)
fold_i += 1
if x_test is not None:
p_test = np.mean(ps_test, axis=0)
print('Finished training {} models '.format(folds))
if x_test is None:
p_test = None
return models, p_train, p_test, scores
In [80]:
classifiers = [
# GradientBoostingClassifier(max_depth=10,subsample=0.8,max_features='auto'),
# MLPClassifier(alpha=0.01,validation_fraction=0.2),
# ExtraTreesClassifier(100,max_depth=10,n_jobs=-1,class_weight='balanced_subsample',bootstrap=True,oob_score=True),
# DecisionTreeClassifier(min_samples_leaf= 3, class_weight ='balanced', max_features=.85, max_leaf_nodes=5, max_depth = 10),
# RandomForestClassifier(n_estimators=100,max_features=.85,n_jobs=-1,class_weight='balanced'),
# AdaBoostClassifier(n_estimators=200, learning_rate=0.15),
# RandomForestClassifier(n_estimators=200,max_features=.85,max_depth=7,n_jobs=-1,class_weight='balanced'),
# LogisticRegression(class_weight='balanced',max_iter=500, multi_class='ovr', n_jobs=-1)
model
]
# Logging for Visual Comparison ( see above cell)
count = 0
for clf in classifiers:
name = clf.__class__.__name__+'{}'.format(count)
print("="*60, name)
models, p_train, p_test, scores = train_k_fold(stack_train, target, clf, stack_test, 7, target)
# stack_test[name] = p_test
# stack_train[name] = p_train
# print("Accuracy: {:.4%}".format(np.mean(scores)))
# log_entry = pd.DataFrame([[name, np.mean(scores)*100]], columns=log_cols)
# log = log.append(log_entry)
# del models, p_train, p_test, scores
count += 1
print(gc.collect())
submit = make_submission(p_test)
submit.to_csv(f'{PATH}\\AV_Stud_2\\stacked_sklearn_showdown.csv', index=False)
submit.head(2)
============================================================ CatBoostClassifier0
Training 7 stratified models on training set (18359, 10) with test set (15021, 10)
Running fold 0, 15735 train samples, 2624 validation samples
0: learn: 0.6481851 total: 64.9ms remaining: 1m 6s
1: learn: 0.6094124 total: 121ms remaining: 1m 1s
2: learn: 0.5760035 total: 187ms remaining: 1m 3s
3: learn: 0.5472214 total: 241ms remaining: 1m 1s
4: learn: 0.5225398 total: 294ms remaining: 59.7s
5: learn: 0.5012622 total: 347ms remaining: 58.7s
6: learn: 0.4828539 total: 400ms remaining: 57.9s
7: learn: 0.4668394 total: 454ms remaining: 57.5s
8: learn: 0.4533647 total: 508ms remaining: 57.1s
9: learn: 0.4415375 total: 562ms remaining: 56.8s
10: learn: 0.4314057 total: 615ms remaining: 56.4s
11: learn: 0.4226526 total: 667ms remaining: 56s
12: learn: 0.4151155 total: 722ms remaining: 56s
13: learn: 0.4084843 total: 778ms remaining: 55.9s
14: learn: 0.4026703 total: 830ms remaining: 55.6s
15: learn: 0.3976716 total: 882ms remaining: 55.4s
16: learn: 0.3934713 total: 934ms remaining: 55.1s
17: learn: 0.3897015 total: 990ms remaining: 55.1s
18: learn: 0.3862878 total: 1.05s remaining: 55.2s
19: learn: 0.3836921 total: 1.08s remaining: 54s
20: learn: 0.3810892 total: 1.13s remaining: 53.9s
21: learn: 0.3788476 total: 1.19s remaining: 53.8s
22: learn: 0.3767785 total: 1.24s remaining: 53.7s
23: learn: 0.3750380 total: 1.29s remaining: 53.5s
24: learn: 0.3734241 total: 1.34s remaining: 53.4s
25: learn: 0.3720517 total: 1.4s remaining: 53.4s
26: learn: 0.3707919 total: 1.45s remaining: 53.2s
27: learn: 0.3697201 total: 1.5s remaining: 53.2s
28: learn: 0.3687587 total: 1.55s remaining: 53s
29: learn: 0.3679110 total: 1.6s remaining: 52.9s
30: learn: 0.3670939 total: 1.66s remaining: 52.8s
31: learn: 0.3663586 total: 1.71s remaining: 52.7s
32: learn: 0.3656937 total: 1.76s remaining: 52.7s
33: learn: 0.3650871 total: 1.81s remaining: 52.6s
34: learn: 0.3645856 total: 1.87s remaining: 52.6s
35: learn: 0.3640861 total: 1.92s remaining: 52.5s
36: learn: 0.3637262 total: 1.97s remaining: 52.4s
37: learn: 0.3632111 total: 2.03s remaining: 52.5s
38: learn: 0.3628977 total: 2.08s remaining: 52.4s
39: learn: 0.3626148 total: 2.14s remaining: 52.4s
40: learn: 0.3623130 total: 2.2s remaining: 52.5s
41: learn: 0.3619653 total: 2.25s remaining: 52.5s
42: learn: 0.3617052 total: 2.31s remaining: 52.4s
43: learn: 0.3615061 total: 2.35s remaining: 52.3s
44: learn: 0.3612979 total: 2.41s remaining: 52.1s
45: learn: 0.3610144 total: 2.46s remaining: 52s
46: learn: 0.3608276 total: 2.51s remaining: 51.9s
47: learn: 0.3606137 total: 2.56s remaining: 51.8s
48: learn: 0.3605021 total: 2.58s remaining: 51.2s
49: learn: 0.3602230 total: 2.66s remaining: 51.6s
50: learn: 0.3600179 total: 2.71s remaining: 51.5s
51: learn: 0.3598236 total: 2.76s remaining: 51.4s
52: learn: 0.3595827 total: 2.81s remaining: 51.4s
53: learn: 0.3593319 total: 2.87s remaining: 51.3s
54: learn: 0.3590494 total: 2.92s remaining: 51.3s
55: learn: 0.3587505 total: 2.98s remaining: 51.3s
56: learn: 0.3584866 total: 3.03s remaining: 51.2s
57: learn: 0.3583369 total: 3.08s remaining: 51.1s
58: learn: 0.3580514 total: 3.14s remaining: 51.1s
59: learn: 0.3578301 total: 3.19s remaining: 51.1s
60: learn: 0.3576421 total: 3.24s remaining: 51s
61: learn: 0.3574939 total: 3.29s remaining: 50.9s
62: learn: 0.3572884 total: 3.35s remaining: 50.8s
63: learn: 0.3571088 total: 3.4s remaining: 50.8s
64: learn: 0.3570246 total: 3.45s remaining: 50.7s
65: learn: 0.3566311 total: 3.5s remaining: 50.6s
66: learn: 0.3563517 total: 3.55s remaining: 50.5s
67: learn: 0.3561758 total: 3.6s remaining: 50.4s
68: learn: 0.3559925 total: 3.65s remaining: 50.3s
69: learn: 0.3556345 total: 3.7s remaining: 50.3s
70: learn: 0.3551581 total: 3.76s remaining: 50.2s
71: learn: 0.3549599 total: 3.81s remaining: 50.2s
72: learn: 0.3548201 total: 3.86s remaining: 50.1s
73: learn: 0.3546627 total: 3.91s remaining: 50s
74: learn: 0.3545299 total: 3.97s remaining: 50s
75: learn: 0.3542640 total: 4.03s remaining: 50s
76: learn: 0.3539824 total: 4.09s remaining: 50s
77: learn: 0.3538001 total: 4.15s remaining: 50.1s
78: learn: 0.3535153 total: 4.22s remaining: 50.3s
79: learn: 0.3533131 total: 4.29s remaining: 50.4s
80: learn: 0.3531736 total: 4.35s remaining: 50.4s
81: learn: 0.3530239 total: 4.4s remaining: 50.4s
82: learn: 0.3528176 total: 4.46s remaining: 50.3s
83: learn: 0.3524394 total: 4.51s remaining: 50.3s
84: learn: 0.3523019 total: 4.57s remaining: 50.2s
85: learn: 0.3519750 total: 4.63s remaining: 50.2s
86: learn: 0.3517176 total: 4.68s remaining: 50.2s
87: learn: 0.3514986 total: 4.74s remaining: 50.2s
88: learn: 0.3512692 total: 4.8s remaining: 50.3s
89: learn: 0.3509997 total: 4.86s remaining: 50.2s
90: learn: 0.3507274 total: 4.93s remaining: 50.3s
91: learn: 0.3504080 total: 4.98s remaining: 50.3s
92: learn: 0.3500977 total: 5.04s remaining: 50.2s
93: learn: 0.3499614 total: 5.09s remaining: 50.2s
94: learn: 0.3497229 total: 5.15s remaining: 50.2s
95: learn: 0.3496327 total: 5.21s remaining: 50.2s
96: learn: 0.3494942 total: 5.28s remaining: 50.3s
97: learn: 0.3492276 total: 5.34s remaining: 50.2s
98: learn: 0.3490245 total: 5.4s remaining: 50.2s
99: learn: 0.3487671 total: 5.46s remaining: 50.2s
100: learn: 0.3485462 total: 5.51s remaining: 50.2s
101: learn: 0.3483539 total: 5.56s remaining: 50.1s
102: learn: 0.3481973 total: 5.62s remaining: 50s
103: learn: 0.3479843 total: 5.67s remaining: 49.9s
104: learn: 0.3477873 total: 5.73s remaining: 50s
105: learn: 0.3476202 total: 5.79s remaining: 49.9s
106: learn: 0.3473025 total: 5.84s remaining: 49.9s
107: learn: 0.3471995 total: 5.91s remaining: 49.9s
108: learn: 0.3470397 total: 5.97s remaining: 49.9s
109: learn: 0.3469315 total: 6.03s remaining: 49.9s
110: learn: 0.3467915 total: 6.09s remaining: 49.9s
111: learn: 0.3466792 total: 6.14s remaining: 49.8s
112: learn: 0.3463831 total: 6.19s remaining: 49.7s
113: learn: 0.3462541 total: 6.25s remaining: 49.7s
114: learn: 0.3460662 total: 6.31s remaining: 49.6s
115: learn: 0.3458561 total: 6.37s remaining: 49.6s
116: learn: 0.3456497 total: 6.43s remaining: 49.6s
117: learn: 0.3455603 total: 6.49s remaining: 49.6s
118: learn: 0.3454544 total: 6.55s remaining: 49.6s
119: learn: 0.3453116 total: 6.6s remaining: 49.5s
120: learn: 0.3452030 total: 6.66s remaining: 49.4s
121: learn: 0.3448862 total: 6.71s remaining: 49.4s
122: learn: 0.3447756 total: 6.76s remaining: 49.3s
123: learn: 0.3446226 total: 6.83s remaining: 49.3s
124: learn: 0.3444308 total: 6.89s remaining: 49.3s
125: learn: 0.3442875 total: 6.95s remaining: 49.3s
126: learn: 0.3441456 total: 7.01s remaining: 49.3s
127: learn: 0.3440239 total: 7.06s remaining: 49.2s
128: learn: 0.3439366 total: 7.12s remaining: 49.1s
129: learn: 0.3438076 total: 7.17s remaining: 49.1s
130: learn: 0.3436073 total: 7.23s remaining: 49s
131: learn: 0.3434326 total: 7.29s remaining: 49s
132: learn: 0.3432817 total: 7.34s remaining: 49s
133: learn: 0.3431327 total: 7.41s remaining: 49s
134: learn: 0.3429686 total: 7.47s remaining: 49s
135: learn: 0.3427217 total: 7.53s remaining: 48.9s
136: learn: 0.3423535 total: 7.58s remaining: 48.9s
137: learn: 0.3420170 total: 7.64s remaining: 48.8s
138: learn: 0.3418232 total: 7.71s remaining: 48.9s
139: learn: 0.3416068 total: 7.77s remaining: 48.8s
140: learn: 0.3413657 total: 7.83s remaining: 48.8s
141: learn: 0.3411805 total: 7.89s remaining: 48.8s
142: learn: 0.3409218 total: 7.96s remaining: 48.9s
143: learn: 0.3407585 total: 8.03s remaining: 48.8s
144: learn: 0.3403750 total: 8.09s remaining: 48.8s
145: learn: 0.3400237 total: 8.14s remaining: 48.8s
146: learn: 0.3396894 total: 8.2s remaining: 48.7s
147: learn: 0.3395618 total: 8.26s remaining: 48.7s
148: learn: 0.3394053 total: 8.32s remaining: 48.6s
149: learn: 0.3391819 total: 8.38s remaining: 48.6s
150: learn: 0.3390379 total: 8.44s remaining: 48.5s
151: learn: 0.3388358 total: 8.49s remaining: 48.5s
152: learn: 0.3385859 total: 8.54s remaining: 48.4s
153: learn: 0.3382192 total: 8.6s remaining: 48.4s
154: learn: 0.3380680 total: 8.65s remaining: 48.3s
155: learn: 0.3378290 total: 8.7s remaining: 48.2s
156: learn: 0.3375538 total: 8.76s remaining: 48.1s
157: learn: 0.3371609 total: 8.82s remaining: 48.1s
158: learn: 0.3370312 total: 8.87s remaining: 48s
159: learn: 0.3369015 total: 8.93s remaining: 48s
160: learn: 0.3367198 total: 8.98s remaining: 47.9s
161: learn: 0.3365333 total: 9.04s remaining: 47.9s
162: learn: 0.3363206 total: 9.09s remaining: 47.8s
163: learn: 0.3361117 total: 9.14s remaining: 47.7s
164: learn: 0.3358580 total: 9.2s remaining: 47.7s
165: learn: 0.3356329 total: 9.26s remaining: 47.6s
166: learn: 0.3353967 total: 9.32s remaining: 47.6s
167: learn: 0.3349739 total: 9.38s remaining: 47.6s
168: learn: 0.3346338 total: 9.43s remaining: 47.5s
169: learn: 0.3343537 total: 9.48s remaining: 47.4s
170: learn: 0.3340408 total: 9.53s remaining: 47.3s
171: learn: 0.3338820 total: 9.59s remaining: 47.3s
172: learn: 0.3337164 total: 9.64s remaining: 47.2s
173: learn: 0.3335392 total: 9.7s remaining: 47.2s
174: learn: 0.3332552 total: 9.76s remaining: 47.1s
175: learn: 0.3331193 total: 9.82s remaining: 47.1s
176: learn: 0.3329150 total: 9.87s remaining: 47s
177: learn: 0.3327256 total: 9.92s remaining: 46.9s
178: learn: 0.3325824 total: 9.98s remaining: 46.9s
179: learn: 0.3324234 total: 10s remaining: 46.8s
180: learn: 0.3323553 total: 10.1s remaining: 46.7s
181: learn: 0.3321465 total: 10.1s remaining: 46.6s
182: learn: 0.3320503 total: 10.2s remaining: 46.5s
183: learn: 0.3317301 total: 10.2s remaining: 46.5s
184: learn: 0.3315445 total: 10.3s remaining: 46.4s
185: learn: 0.3313328 total: 10.3s remaining: 46.4s
186: learn: 0.3311904 total: 10.4s remaining: 46.3s
187: learn: 0.3309772 total: 10.5s remaining: 46.3s
188: learn: 0.3308576 total: 10.5s remaining: 46.3s
189: learn: 0.3307856 total: 10.6s remaining: 46.2s
190: learn: 0.3305994 total: 10.6s remaining: 46.2s
191: learn: 0.3300575 total: 10.7s remaining: 46.1s
192: learn: 0.3298324 total: 10.7s remaining: 46s
193: learn: 0.3294752 total: 10.8s remaining: 45.9s
194: learn: 0.3292323 total: 10.8s remaining: 45.8s
195: learn: 0.3290874 total: 10.9s remaining: 45.8s
196: learn: 0.3289844 total: 10.9s remaining: 45.7s
197: learn: 0.3287152 total: 11s remaining: 45.6s
198: learn: 0.3285793 total: 11s remaining: 45.5s
199: learn: 0.3282735 total: 11.1s remaining: 45.4s
200: learn: 0.3280203 total: 11.1s remaining: 45.4s
201: learn: 0.3276553 total: 11.2s remaining: 45.3s
202: learn: 0.3273333 total: 11.2s remaining: 45.2s
203: learn: 0.3271358 total: 11.3s remaining: 45.1s
204: learn: 0.3267434 total: 11.3s remaining: 45.1s
205: learn: 0.3265670 total: 11.4s remaining: 45s
206: learn: 0.3263327 total: 11.4s remaining: 44.9s
207: learn: 0.3260417 total: 11.5s remaining: 44.8s
208: learn: 0.3258267 total: 11.5s remaining: 44.7s
209: learn: 0.3256858 total: 11.6s remaining: 44.7s
210: learn: 0.3254350 total: 11.6s remaining: 44.6s
211: learn: 0.3252797 total: 11.7s remaining: 44.7s
212: learn: 0.3251354 total: 11.8s remaining: 44.6s
213: learn: 0.3249029 total: 11.8s remaining: 44.6s
214: learn: 0.3244966 total: 11.9s remaining: 44.6s
215: learn: 0.3243638 total: 12s remaining: 44.5s
216: learn: 0.3240779 total: 12s remaining: 44.5s
217: learn: 0.3237119 total: 12.1s remaining: 44.4s
218: learn: 0.3236427 total: 12.1s remaining: 44.3s
219: learn: 0.3234143 total: 12.2s remaining: 44.3s
220: learn: 0.3231034 total: 12.2s remaining: 44.2s
221: learn: 0.3228841 total: 12.3s remaining: 44.1s
222: learn: 0.3227370 total: 12.3s remaining: 44s
223: learn: 0.3225730 total: 12.4s remaining: 44s
224: learn: 0.3224182 total: 12.4s remaining: 43.9s
225: learn: 0.3223328 total: 12.5s remaining: 43.8s
226: learn: 0.3220583 total: 12.5s remaining: 43.7s
227: learn: 0.3218176 total: 12.6s remaining: 43.7s
228: learn: 0.3217073 total: 12.6s remaining: 43.6s
229: learn: 0.3215389 total: 12.7s remaining: 43.6s
230: learn: 0.3213897 total: 12.7s remaining: 43.5s
231: learn: 0.3211568 total: 12.8s remaining: 43.5s
232: learn: 0.3209335 total: 12.9s remaining: 43.4s
233: learn: 0.3207118 total: 12.9s remaining: 43.4s
234: learn: 0.3205800 total: 13s remaining: 43.4s
235: learn: 0.3202968 total: 13s remaining: 43.3s
236: learn: 0.3201682 total: 13.1s remaining: 43.3s
237: learn: 0.3200129 total: 13.1s remaining: 43.2s
238: learn: 0.3198364 total: 13.2s remaining: 43.1s
239: learn: 0.3196699 total: 13.3s remaining: 43.1s
240: learn: 0.3195113 total: 13.3s remaining: 43s
241: learn: 0.3193040 total: 13.4s remaining: 43s
242: learn: 0.3190997 total: 13.4s remaining: 42.9s
243: learn: 0.3189002 total: 13.5s remaining: 42.9s
244: learn: 0.3187978 total: 13.5s remaining: 42.8s
245: learn: 0.3185554 total: 13.6s remaining: 42.8s
246: learn: 0.3184003 total: 13.6s remaining: 42.7s
247: learn: 0.3181440 total: 13.7s remaining: 42.6s
248: learn: 0.3179112 total: 13.7s remaining: 42.6s
249: learn: 0.3176249 total: 13.8s remaining: 42.5s
250: learn: 0.3175342 total: 13.8s remaining: 42.4s
251: learn: 0.3172621 total: 13.9s remaining: 42.4s
252: learn: 0.3170375 total: 14s remaining: 42.4s
253: learn: 0.3168724 total: 14s remaining: 42.3s
254: learn: 0.3165515 total: 14.1s remaining: 42.3s
255: learn: 0.3164369 total: 14.1s remaining: 42.2s
256: learn: 0.3163414 total: 14.2s remaining: 42.2s
257: learn: 0.3161923 total: 14.2s remaining: 42.1s
258: learn: 0.3160302 total: 14.3s remaining: 42s
259: learn: 0.3159043 total: 14.3s remaining: 41.9s
260: learn: 0.3157439 total: 14.4s remaining: 41.9s
261: learn: 0.3155963 total: 14.5s remaining: 41.8s
262: learn: 0.3154539 total: 14.5s remaining: 41.8s
263: learn: 0.3152198 total: 14.6s remaining: 41.7s
264: learn: 0.3151070 total: 14.6s remaining: 41.7s
265: learn: 0.3148861 total: 14.7s remaining: 41.6s
266: learn: 0.3147456 total: 14.7s remaining: 41.6s
267: learn: 0.3144285 total: 14.8s remaining: 41.5s
268: learn: 0.3142692 total: 14.8s remaining: 41.4s
269: learn: 0.3141520 total: 14.9s remaining: 41.4s
270: learn: 0.3140115 total: 14.9s remaining: 41.3s
271: learn: 0.3138097 total: 15s remaining: 41.2s
272: learn: 0.3135332 total: 15.1s remaining: 41.2s
273: learn: 0.3133191 total: 15.1s remaining: 41.2s
274: learn: 0.3132111 total: 15.2s remaining: 41.1s
275: learn: 0.3130501 total: 15.2s remaining: 41s
276: learn: 0.3128447 total: 15.3s remaining: 41s
277: learn: 0.3124909 total: 15.3s remaining: 40.9s
278: learn: 0.3123479 total: 15.4s remaining: 40.8s
279: learn: 0.3121660 total: 15.4s remaining: 40.8s
280: learn: 0.3120796 total: 15.5s remaining: 40.8s
281: learn: 0.3119504 total: 15.6s remaining: 40.7s
282: learn: 0.3118529 total: 15.6s remaining: 40.6s
283: learn: 0.3115989 total: 15.7s remaining: 40.6s
284: learn: 0.3114462 total: 15.7s remaining: 40.5s
285: learn: 0.3113249 total: 15.8s remaining: 40.5s
286: learn: 0.3112033 total: 15.8s remaining: 40.4s
287: learn: 0.3110453 total: 15.9s remaining: 40.4s
288: learn: 0.3108303 total: 15.9s remaining: 40.3s
289: learn: 0.3106511 total: 16s remaining: 40.3s
290: learn: 0.3104685 total: 16.1s remaining: 40.2s
291: learn: 0.3100525 total: 16.1s remaining: 40.2s
292: learn: 0.3099637 total: 16.2s remaining: 40.1s
293: learn: 0.3098070 total: 16.2s remaining: 40.1s
294: learn: 0.3096170 total: 16.3s remaining: 40s
295: learn: 0.3095174 total: 16.3s remaining: 40s
296: learn: 0.3093688 total: 16.4s remaining: 39.9s
297: learn: 0.3092152 total: 16.4s remaining: 39.8s
298: learn: 0.3090751 total: 16.5s remaining: 39.8s
299: learn: 0.3089930 total: 16.5s remaining: 39.7s
300: learn: 0.3088097 total: 16.6s remaining: 39.6s
301: learn: 0.3086924 total: 16.6s remaining: 39.6s
302: learn: 0.3083659 total: 16.7s remaining: 39.5s
303: learn: 0.3082719 total: 16.8s remaining: 39.5s
304: learn: 0.3081131 total: 16.8s remaining: 39.4s
305: learn: 0.3078491 total: 16.9s remaining: 39.4s
306: learn: 0.3077287 total: 16.9s remaining: 39.3s
307: learn: 0.3076336 total: 17s remaining: 39.3s
308: learn: 0.3074929 total: 17s remaining: 39.2s
309: learn: 0.3072404 total: 17.1s remaining: 39.2s
310: learn: 0.3070429 total: 17.1s remaining: 39.1s
311: learn: 0.3067701 total: 17.2s remaining: 39s
312: learn: 0.3065063 total: 17.3s remaining: 39s
313: learn: 0.3063273 total: 17.3s remaining: 39s
314: learn: 0.3061040 total: 17.4s remaining: 38.9s
315: learn: 0.3059111 total: 17.4s remaining: 38.9s
316: learn: 0.3057716 total: 17.5s remaining: 38.8s
317: learn: 0.3056827 total: 17.6s remaining: 38.8s
318: learn: 0.3055169 total: 17.6s remaining: 38.7s
319: learn: 0.3051994 total: 17.7s remaining: 38.6s
320: learn: 0.3051130 total: 17.7s remaining: 38.6s
321: learn: 0.3049854 total: 17.8s remaining: 38.5s
322: learn: 0.3048600 total: 17.8s remaining: 38.5s
323: learn: 0.3047321 total: 17.9s remaining: 38.4s
324: learn: 0.3046151 total: 17.9s remaining: 38.4s
325: learn: 0.3044832 total: 18s remaining: 38.3s
326: learn: 0.3043078 total: 18.1s remaining: 38.3s
327: learn: 0.3041846 total: 18.1s remaining: 38.2s
328: learn: 0.3040707 total: 18.2s remaining: 38.1s
329: learn: 0.3039529 total: 18.2s remaining: 38.1s
330: learn: 0.3038453 total: 18.3s remaining: 38s
331: learn: 0.3037811 total: 18.3s remaining: 37.9s
332: learn: 0.3037244 total: 18.4s remaining: 37.9s
333: learn: 0.3036491 total: 18.4s remaining: 37.8s
334: learn: 0.3033735 total: 18.5s remaining: 37.8s
335: learn: 0.3032250 total: 18.6s remaining: 37.8s
336: learn: 0.3029898 total: 18.6s remaining: 37.8s
337: learn: 0.3028837 total: 18.7s remaining: 37.7s
338: learn: 0.3027754 total: 18.7s remaining: 37.6s
339: learn: 0.3026537 total: 18.8s remaining: 37.6s
340: learn: 0.3025499 total: 18.8s remaining: 37.5s
341: learn: 0.3023848 total: 18.9s remaining: 37.5s
342: learn: 0.3023323 total: 19s remaining: 37.4s
343: learn: 0.3022730 total: 19s remaining: 37.4s
344: learn: 0.3022005 total: 19.1s remaining: 37.3s
345: learn: 0.3021247 total: 19.1s remaining: 37.3s
346: learn: 0.3020700 total: 19.2s remaining: 37.2s
347: learn: 0.3020103 total: 19.2s remaining: 37.2s
348: learn: 0.3019041 total: 19.3s remaining: 37.1s
349: learn: 0.3017364 total: 19.3s remaining: 37s
350: learn: 0.3016022 total: 19.4s remaining: 37s
351: learn: 0.3014905 total: 19.4s remaining: 36.9s
352: learn: 0.3013469 total: 19.5s remaining: 36.8s
353: learn: 0.3012472 total: 19.5s remaining: 36.8s
354: learn: 0.3010402 total: 19.6s remaining: 36.7s
355: learn: 0.3006224 total: 19.6s remaining: 36.6s
356: learn: 0.3004914 total: 19.7s remaining: 36.6s
357: learn: 0.3002891 total: 19.7s remaining: 36.5s
358: learn: 0.3001955 total: 19.8s remaining: 36.4s
359: learn: 0.3001178 total: 19.8s remaining: 36.4s
360: learn: 0.3000352 total: 19.9s remaining: 36.3s
361: learn: 0.2999471 total: 20s remaining: 36.3s
362: learn: 0.2998009 total: 20s remaining: 36.2s
363: learn: 0.2996920 total: 20.1s remaining: 36.2s
364: learn: 0.2995773 total: 20.1s remaining: 36.2s
365: learn: 0.2994309 total: 20.2s remaining: 36.1s
366: learn: 0.2993324 total: 20.3s remaining: 36.1s
367: learn: 0.2992658 total: 20.3s remaining: 36s
368: learn: 0.2991016 total: 20.4s remaining: 35.9s
369: learn: 0.2988225 total: 20.4s remaining: 35.9s
370: learn: 0.2986893 total: 20.5s remaining: 35.8s
371: learn: 0.2985883 total: 20.5s remaining: 35.8s
372: learn: 0.2983971 total: 20.6s remaining: 35.7s
373: learn: 0.2981525 total: 20.6s remaining: 35.6s
374: learn: 0.2979503 total: 20.7s remaining: 35.6s
375: learn: 0.2978791 total: 20.7s remaining: 35.5s
376: learn: 0.2977887 total: 20.8s remaining: 35.5s
377: learn: 0.2977007 total: 20.9s remaining: 35.4s
378: learn: 0.2976359 total: 20.9s remaining: 35.4s
379: learn: 0.2975521 total: 21s remaining: 35.3s
380: learn: 0.2974108 total: 21s remaining: 35.3s
381: learn: 0.2972868 total: 21.1s remaining: 35.2s
382: learn: 0.2971518 total: 21.1s remaining: 35.1s
383: learn: 0.2970974 total: 21.2s remaining: 35.1s
384: learn: 0.2968659 total: 21.2s remaining: 35s
385: learn: 0.2966912 total: 21.3s remaining: 34.9s
386: learn: 0.2965146 total: 21.3s remaining: 34.9s
387: learn: 0.2964730 total: 21.4s remaining: 34.8s
388: learn: 0.2963467 total: 21.4s remaining: 34.8s
389: learn: 0.2962065 total: 21.5s remaining: 34.7s
390: learn: 0.2960820 total: 21.5s remaining: 34.6s
391: learn: 0.2959340 total: 21.6s remaining: 34.6s
392: learn: 0.2957384 total: 21.6s remaining: 34.5s
393: learn: 0.2957107 total: 21.7s remaining: 34.4s
394: learn: 0.2956360 total: 21.7s remaining: 34.4s
395: learn: 0.2955839 total: 21.8s remaining: 34.3s
396: learn: 0.2955016 total: 21.8s remaining: 34.3s
397: learn: 0.2953892 total: 21.9s remaining: 34.2s
398: learn: 0.2953718 total: 21.9s remaining: 34.2s
399: learn: 0.2952572 total: 22s remaining: 34.1s
400: learn: 0.2951538 total: 22.1s remaining: 34s
401: learn: 0.2950701 total: 22.1s remaining: 34s
402: learn: 0.2950315 total: 22.2s remaining: 34s
403: learn: 0.2948882 total: 22.2s remaining: 33.9s
404: learn: 0.2948071 total: 22.3s remaining: 33.8s
405: learn: 0.2946854 total: 22.3s remaining: 33.8s
406: learn: 0.2945666 total: 22.4s remaining: 33.7s
407: learn: 0.2944200 total: 22.4s remaining: 33.7s
408: learn: 0.2942997 total: 22.5s remaining: 33.6s
409: learn: 0.2941641 total: 22.5s remaining: 33.5s
410: learn: 0.2940621 total: 22.6s remaining: 33.5s
411: learn: 0.2939070 total: 22.6s remaining: 33.4s
412: learn: 0.2937650 total: 22.7s remaining: 33.3s
413: learn: 0.2937054 total: 22.7s remaining: 33.3s
414: learn: 0.2935713 total: 22.8s remaining: 33.2s
415: learn: 0.2934991 total: 22.8s remaining: 33.2s
416: learn: 0.2934001 total: 22.9s remaining: 33.1s
417: learn: 0.2933202 total: 23s remaining: 33.1s
418: learn: 0.2932339 total: 23s remaining: 33s
419: learn: 0.2931612 total: 23.1s remaining: 33s
420: learn: 0.2930626 total: 23.1s remaining: 32.9s
421: learn: 0.2929196 total: 23.2s remaining: 32.8s
422: learn: 0.2928496 total: 23.2s remaining: 32.8s
423: learn: 0.2926915 total: 23.3s remaining: 32.7s
424: learn: 0.2924024 total: 23.3s remaining: 32.7s
425: learn: 0.2921415 total: 23.4s remaining: 32.6s
426: learn: 0.2920066 total: 23.4s remaining: 32.5s
427: learn: 0.2918888 total: 23.5s remaining: 32.5s
428: learn: 0.2917993 total: 23.5s remaining: 32.4s
429: learn: 0.2916843 total: 23.6s remaining: 32.4s
430: learn: 0.2915767 total: 23.6s remaining: 32.3s
431: learn: 0.2914000 total: 23.7s remaining: 32.3s
432: learn: 0.2912126 total: 23.7s remaining: 32.2s
433: learn: 0.2910799 total: 23.8s remaining: 32.1s
434: learn: 0.2908742 total: 23.8s remaining: 32.1s
435: learn: 0.2906511 total: 23.9s remaining: 32s
436: learn: 0.2906189 total: 23.9s remaining: 31.9s
437: learn: 0.2905809 total: 24s remaining: 31.9s
438: learn: 0.2904010 total: 24.1s remaining: 31.8s
439: learn: 0.2902770 total: 24.1s remaining: 31.8s
440: learn: 0.2901526 total: 24.2s remaining: 31.7s
441: learn: 0.2900519 total: 24.2s remaining: 31.7s
442: learn: 0.2899846 total: 24.3s remaining: 31.6s
443: learn: 0.2898919 total: 24.3s remaining: 31.6s
444: learn: 0.2896774 total: 24.4s remaining: 31.5s
445: learn: 0.2895957 total: 24.4s remaining: 31.5s
446: learn: 0.2894225 total: 24.5s remaining: 31.4s
447: learn: 0.2893107 total: 24.5s remaining: 31.3s
448: learn: 0.2891357 total: 24.6s remaining: 31.3s
449: learn: 0.2888844 total: 24.6s remaining: 31.2s
450: learn: 0.2887993 total: 24.7s remaining: 31.2s
451: learn: 0.2886211 total: 24.7s remaining: 31.1s
452: learn: 0.2885344 total: 24.8s remaining: 31s
453: learn: 0.2884875 total: 24.8s remaining: 31s
454: learn: 0.2883867 total: 24.9s remaining: 30.9s
455: learn: 0.2882355 total: 25s remaining: 30.9s
456: learn: 0.2881273 total: 25s remaining: 30.8s
457: learn: 0.2880021 total: 25.1s remaining: 30.8s
458: learn: 0.2878264 total: 25.1s remaining: 30.7s
459: learn: 0.2876864 total: 25.2s remaining: 30.7s
460: learn: 0.2875899 total: 25.2s remaining: 30.6s
461: learn: 0.2874296 total: 25.3s remaining: 30.6s
462: learn: 0.2872318 total: 25.4s remaining: 30.5s
463: learn: 0.2871120 total: 25.4s remaining: 30.4s
464: learn: 0.2868254 total: 25.5s remaining: 30.4s
465: learn: 0.2868211 total: 25.5s remaining: 30.3s
466: learn: 0.2865913 total: 25.6s remaining: 30.3s
467: learn: 0.2864217 total: 25.6s remaining: 30.2s
468: learn: 0.2862783 total: 25.7s remaining: 30.1s
469: learn: 0.2861777 total: 25.7s remaining: 30.1s
470: learn: 0.2861006 total: 25.8s remaining: 30s
471: learn: 0.2859760 total: 25.8s remaining: 30s
472: learn: 0.2858622 total: 25.9s remaining: 29.9s
473: learn: 0.2857871 total: 25.9s remaining: 29.9s
474: learn: 0.2856013 total: 26s remaining: 29.8s
475: learn: 0.2855398 total: 26s remaining: 29.7s
476: learn: 0.2854337 total: 26.1s remaining: 29.7s
477: learn: 0.2852846 total: 26.1s remaining: 29.6s
478: learn: 0.2851864 total: 26.2s remaining: 29.6s
479: learn: 0.2850513 total: 26.2s remaining: 29.5s
480: learn: 0.2849473 total: 26.3s remaining: 29.5s
481: learn: 0.2848752 total: 26.4s remaining: 29.4s
482: learn: 0.2847960 total: 26.4s remaining: 29.4s
483: learn: 0.2847650 total: 26.5s remaining: 29.3s
484: learn: 0.2846974 total: 26.6s remaining: 29.3s
485: learn: 0.2846002 total: 26.6s remaining: 29.3s
486: learn: 0.2844568 total: 26.7s remaining: 29.2s
487: learn: 0.2843299 total: 26.7s remaining: 29.1s
488: learn: 0.2842862 total: 26.8s remaining: 29.1s
489: learn: 0.2841858 total: 26.8s remaining: 29s
490: learn: 0.2841266 total: 26.9s remaining: 29s
491: learn: 0.2840770 total: 27s remaining: 28.9s
492: learn: 0.2840619 total: 27s remaining: 28.9s
493: learn: 0.2839793 total: 27.1s remaining: 28.8s
494: learn: 0.2838372 total: 27.1s remaining: 28.8s
495: learn: 0.2837385 total: 27.2s remaining: 28.7s
496: learn: 0.2836576 total: 27.2s remaining: 28.7s
497: learn: 0.2835777 total: 27.3s remaining: 28.6s
498: learn: 0.2835211 total: 27.3s remaining: 28.5s
499: learn: 0.2834801 total: 27.4s remaining: 28.5s
500: learn: 0.2833408 total: 27.4s remaining: 28.4s
501: learn: 0.2832605 total: 27.5s remaining: 28.4s
502: learn: 0.2831486 total: 27.5s remaining: 28.3s
503: learn: 0.2830622 total: 27.6s remaining: 28.3s
504: learn: 0.2830136 total: 27.6s remaining: 28.2s
505: learn: 0.2829457 total: 27.7s remaining: 28.1s
506: learn: 0.2828529 total: 27.8s remaining: 28.1s
507: learn: 0.2827136 total: 27.8s remaining: 28s
508: learn: 0.2826194 total: 27.9s remaining: 28s
509: learn: 0.2825590 total: 27.9s remaining: 27.9s
510: learn: 0.2824660 total: 28s remaining: 27.9s
511: learn: 0.2822875 total: 28.1s remaining: 27.8s
512: learn: 0.2820940 total: 28.1s remaining: 27.8s
513: learn: 0.2819821 total: 28.2s remaining: 27.7s
514: learn: 0.2819289 total: 28.2s remaining: 27.7s
515: learn: 0.2819283 total: 28.2s remaining: 27.6s
516: learn: 0.2817388 total: 28.3s remaining: 27.5s
517: learn: 0.2815865 total: 28.3s remaining: 27.5s
518: learn: 0.2815205 total: 28.4s remaining: 27.4s
519: learn: 0.2815202 total: 28.4s remaining: 27.3s
520: learn: 0.2814596 total: 28.5s remaining: 27.3s
521: learn: 0.2813749 total: 28.5s remaining: 27.2s
522: learn: 0.2812095 total: 28.6s remaining: 27.2s
523: learn: 0.2811652 total: 28.7s remaining: 27.1s
524: learn: 0.2810710 total: 28.7s remaining: 27.1s
525: learn: 0.2809899 total: 28.8s remaining: 27s
526: learn: 0.2808179 total: 28.8s remaining: 27s
527: learn: 0.2807271 total: 28.9s remaining: 26.9s
528: learn: 0.2806304 total: 28.9s remaining: 26.9s
529: learn: 0.2805216 total: 29s remaining: 26.8s
530: learn: 0.2803013 total: 29.1s remaining: 26.8s
531: learn: 0.2802025 total: 29.1s remaining: 26.7s
532: learn: 0.2800958 total: 29.2s remaining: 26.7s
533: learn: 0.2800154 total: 29.3s remaining: 26.6s
534: learn: 0.2799977 total: 29.3s remaining: 26.6s
535: learn: 0.2799899 total: 29.4s remaining: 26.5s
536: learn: 0.2798905 total: 29.4s remaining: 26.4s
537: learn: 0.2798270 total: 29.5s remaining: 26.4s
538: learn: 0.2797870 total: 29.5s remaining: 26.3s
539: learn: 0.2797071 total: 29.6s remaining: 26.3s
540: learn: 0.2796429 total: 29.6s remaining: 26.2s
541: learn: 0.2794233 total: 29.7s remaining: 26.2s
542: learn: 0.2792850 total: 29.7s remaining: 26.1s
543: learn: 0.2791719 total: 29.8s remaining: 26.1s
544: learn: 0.2791217 total: 29.8s remaining: 26s
545: learn: 0.2790502 total: 29.9s remaining: 26s
546: learn: 0.2789600 total: 30s remaining: 25.9s
547: learn: 0.2789260 total: 30s remaining: 25.9s
548: learn: 0.2788654 total: 30.1s remaining: 25.8s
549: learn: 0.2787942 total: 30.1s remaining: 25.7s
550: learn: 0.2786892 total: 30.2s remaining: 25.7s
551: learn: 0.2786114 total: 30.2s remaining: 25.6s
552: learn: 0.2785574 total: 30.3s remaining: 25.6s
553: learn: 0.2784611 total: 30.3s remaining: 25.5s
554: learn: 0.2783523 total: 30.4s remaining: 25.5s
555: learn: 0.2783141 total: 30.4s remaining: 25.4s
556: learn: 0.2782761 total: 30.5s remaining: 25.4s
557: learn: 0.2781695 total: 30.6s remaining: 25.3s
558: learn: 0.2781620 total: 30.6s remaining: 25.2s
559: learn: 0.2780430 total: 30.6s remaining: 25.2s
560: learn: 0.2779266 total: 30.7s remaining: 25.1s
561: learn: 0.2778842 total: 30.7s remaining: 25.1s
562: learn: 0.2778841 total: 30.8s remaining: 25s
563: learn: 0.2777149 total: 30.8s remaining: 24.9s
564: learn: 0.2776938 total: 30.9s remaining: 24.9s
565: learn: 0.2775796 total: 30.9s remaining: 24.8s
566: learn: 0.2775304 total: 31s remaining: 24.7s
567: learn: 0.2774014 total: 31s remaining: 24.7s
568: learn: 0.2773577 total: 31.1s remaining: 24.6s
569: learn: 0.2773013 total: 31.1s remaining: 24.6s
570: learn: 0.2772583 total: 31.2s remaining: 24.5s
571: learn: 0.2770435 total: 31.3s remaining: 24.5s
572: learn: 0.2768955 total: 31.3s remaining: 24.4s
573: learn: 0.2768281 total: 31.4s remaining: 24.4s
574: learn: 0.2767562 total: 31.4s remaining: 24.3s
575: learn: 0.2766833 total: 31.5s remaining: 24.3s
576: learn: 0.2765713 total: 31.5s remaining: 24.2s
577: learn: 0.2763676 total: 31.6s remaining: 24.1s
578: learn: 0.2762637 total: 31.6s remaining: 24.1s
579: learn: 0.2761498 total: 31.7s remaining: 24s
580: learn: 0.2761451 total: 31.7s remaining: 24s
581: learn: 0.2761020 total: 31.8s remaining: 23.9s
582: learn: 0.2759931 total: 31.8s remaining: 23.8s
583: learn: 0.2759919 total: 31.8s remaining: 23.8s
584: learn: 0.2759047 total: 31.9s remaining: 23.7s
585: learn: 0.2758099 total: 31.9s remaining: 23.7s
586: learn: 0.2757913 total: 32s remaining: 23.6s
587: learn: 0.2757076 total: 32s remaining: 23.5s
588: learn: 0.2756429 total: 32.1s remaining: 23.5s
589: learn: 0.2755547 total: 32.2s remaining: 23.4s
590: learn: 0.2754945 total: 32.2s remaining: 23.4s
591: learn: 0.2752887 total: 32.3s remaining: 23.3s
592: learn: 0.2752705 total: 32.3s remaining: 23.3s
593: learn: 0.2752012 total: 32.4s remaining: 23.2s
594: learn: 0.2751646 total: 32.4s remaining: 23.2s
595: learn: 0.2750020 total: 32.5s remaining: 23.1s
596: learn: 0.2750020 total: 32.5s remaining: 23s
597: learn: 0.2748070 total: 32.6s remaining: 23s
598: learn: 0.2747283 total: 32.6s remaining: 22.9s
599: learn: 0.2746424 total: 32.7s remaining: 22.9s
600: learn: 0.2745996 total: 32.7s remaining: 22.8s
601: learn: 0.2744458 total: 32.8s remaining: 22.7s
602: learn: 0.2744455 total: 32.8s remaining: 22.7s
603: learn: 0.2743149 total: 32.8s remaining: 22.6s
604: learn: 0.2741778 total: 32.9s remaining: 22.6s
605: learn: 0.2741211 total: 32.9s remaining: 22.5s
606: learn: 0.2740172 total: 33s remaining: 22.4s
607: learn: 0.2738582 total: 33s remaining: 22.4s
608: learn: 0.2737915 total: 33.1s remaining: 22.3s
609: learn: 0.2737192 total: 33.2s remaining: 22.3s
610: learn: 0.2736744 total: 33.2s remaining: 22.2s
611: learn: 0.2735607 total: 33.3s remaining: 22.2s
612: learn: 0.2734362 total: 33.3s remaining: 22.1s
613: learn: 0.2734188 total: 33.4s remaining: 22.1s
614: learn: 0.2733012 total: 33.4s remaining: 22s
615: learn: 0.2731765 total: 33.5s remaining: 22s
616: learn: 0.2730615 total: 33.5s remaining: 21.9s
617: learn: 0.2730371 total: 33.6s remaining: 21.8s
618: learn: 0.2730048 total: 33.6s remaining: 21.8s
619: learn: 0.2729383 total: 33.7s remaining: 21.7s
620: learn: 0.2728824 total: 33.8s remaining: 21.7s
621: learn: 0.2727980 total: 33.8s remaining: 21.6s
622: learn: 0.2727173 total: 33.9s remaining: 21.6s
623: learn: 0.2726533 total: 33.9s remaining: 21.5s
624: learn: 0.2726290 total: 34s remaining: 21.5s
625: learn: 0.2725291 total: 34s remaining: 21.4s
626: learn: 0.2724211 total: 34.1s remaining: 21.4s
627: learn: 0.2723158 total: 34.1s remaining: 21.3s
628: learn: 0.2722388 total: 34.2s remaining: 21.2s
629: learn: 0.2722232 total: 34.2s remaining: 21.2s
630: learn: 0.2721708 total: 34.3s remaining: 21.1s
631: learn: 0.2720854 total: 34.3s remaining: 21.1s
632: learn: 0.2720662 total: 34.4s remaining: 21s
633: learn: 0.2719748 total: 34.5s remaining: 21s
634: learn: 0.2719105 total: 34.5s remaining: 20.9s
635: learn: 0.2718100 total: 34.6s remaining: 20.9s
636: learn: 0.2716541 total: 34.6s remaining: 20.8s
637: learn: 0.2715708 total: 34.7s remaining: 20.8s
638: learn: 0.2714615 total: 34.7s remaining: 20.7s
639: learn: 0.2714590 total: 34.8s remaining: 20.7s
640: learn: 0.2714068 total: 34.8s remaining: 20.6s
641: learn: 0.2713250 total: 34.9s remaining: 20.5s
642: learn: 0.2713188 total: 34.9s remaining: 20.5s
643: learn: 0.2712659 total: 35s remaining: 20.4s
644: learn: 0.2712095 total: 35s remaining: 20.4s
645: learn: 0.2710945 total: 35.1s remaining: 20.3s
646: learn: 0.2710698 total: 35.1s remaining: 20.3s
647: learn: 0.2709912 total: 35.2s remaining: 20.2s
648: learn: 0.2709555 total: 35.2s remaining: 20.1s
649: learn: 0.2709171 total: 35.3s remaining: 20.1s
650: learn: 0.2708217 total: 35.3s remaining: 20s
651: learn: 0.2706892 total: 35.4s remaining: 20s
652: learn: 0.2706406 total: 35.5s remaining: 19.9s
653: learn: 0.2705672 total: 35.5s remaining: 19.9s
654: learn: 0.2705633 total: 35.6s remaining: 19.8s
655: learn: 0.2705629 total: 35.6s remaining: 19.8s
656: learn: 0.2704771 total: 35.7s remaining: 19.7s
657: learn: 0.2703987 total: 35.7s remaining: 19.7s
658: learn: 0.2703987 total: 35.7s remaining: 19.6s
659: learn: 0.2702922 total: 35.8s remaining: 19.5s
660: learn: 0.2702447 total: 35.9s remaining: 19.5s
661: learn: 0.2702100 total: 35.9s remaining: 19.4s
662: learn: 0.2701836 total: 36s remaining: 19.4s
663: learn: 0.2701792 total: 36s remaining: 19.3s
664: learn: 0.2701539 total: 36.1s remaining: 19.3s
665: learn: 0.2700551 total: 36.1s remaining: 19.2s
666: learn: 0.2698844 total: 36.2s remaining: 19.2s
667: learn: 0.2698208 total: 36.2s remaining: 19.1s
668: learn: 0.2697748 total: 36.3s remaining: 19s
669: learn: 0.2696888 total: 36.3s remaining: 19s
670: learn: 0.2696362 total: 36.4s remaining: 18.9s
671: learn: 0.2693947 total: 36.4s remaining: 18.9s
672: learn: 0.2693406 total: 36.5s remaining: 18.8s
673: learn: 0.2693400 total: 36.5s remaining: 18.7s
674: learn: 0.2692739 total: 36.6s remaining: 18.7s
675: learn: 0.2692135 total: 36.6s remaining: 18.6s
676: learn: 0.2691459 total: 36.7s remaining: 18.6s
677: learn: 0.2691250 total: 36.7s remaining: 18.5s
678: learn: 0.2690631 total: 36.8s remaining: 18.5s
679: learn: 0.2689923 total: 36.8s remaining: 18.4s
680: learn: 0.2689596 total: 36.9s remaining: 18.4s
681: learn: 0.2689341 total: 36.9s remaining: 18.3s
682: learn: 0.2687686 total: 37s remaining: 18.3s
683: learn: 0.2686715 total: 37s remaining: 18.2s
684: learn: 0.2685418 total: 37.1s remaining: 18.1s
685: learn: 0.2685165 total: 37.1s remaining: 18.1s
686: learn: 0.2684888 total: 37.2s remaining: 18s
687: learn: 0.2684154 total: 37.2s remaining: 18s
688: learn: 0.2683745 total: 37.3s remaining: 17.9s
689: learn: 0.2683257 total: 37.3s remaining: 17.9s
690: learn: 0.2682934 total: 37.4s remaining: 17.8s
691: learn: 0.2681039 total: 37.4s remaining: 17.7s
692: learn: 0.2680054 total: 37.5s remaining: 17.7s
693: learn: 0.2678730 total: 37.5s remaining: 17.6s
694: learn: 0.2678278 total: 37.6s remaining: 17.6s
695: learn: 0.2677565 total: 37.6s remaining: 17.5s
696: learn: 0.2677564 total: 37.6s remaining: 17.4s
697: learn: 0.2676763 total: 37.7s remaining: 17.4s
698: learn: 0.2676373 total: 37.7s remaining: 17.3s
699: learn: 0.2675651 total: 37.8s remaining: 17.3s
700: learn: 0.2675216 total: 37.8s remaining: 17.2s
701: learn: 0.2674201 total: 37.9s remaining: 17.2s
702: learn: 0.2672518 total: 38s remaining: 17.1s
703: learn: 0.2672362 total: 38s remaining: 17.1s
704: learn: 0.2672195 total: 38.1s remaining: 17s
705: learn: 0.2671334 total: 38.1s remaining: 16.9s
706: learn: 0.2671334 total: 38.1s remaining: 16.9s
707: learn: 0.2670280 total: 38.2s remaining: 16.8s
708: learn: 0.2670191 total: 38.2s remaining: 16.8s
709: learn: 0.2669496 total: 38.3s remaining: 16.7s
710: learn: 0.2668933 total: 38.3s remaining: 16.6s
711: learn: 0.2668095 total: 38.4s remaining: 16.6s
712: learn: 0.2667322 total: 38.4s remaining: 16.5s
713: learn: 0.2667135 total: 38.5s remaining: 16.5s
714: learn: 0.2666092 total: 38.5s remaining: 16.4s
715: learn: 0.2665454 total: 38.6s remaining: 16.4s
716: learn: 0.2664706 total: 38.6s remaining: 16.3s
717: learn: 0.2663655 total: 38.7s remaining: 16.3s
718: learn: 0.2663250 total: 38.7s remaining: 16.2s
719: learn: 0.2663248 total: 38.7s remaining: 16.1s
720: learn: 0.2662972 total: 38.8s remaining: 16.1s
721: learn: 0.2662635 total: 38.8s remaining: 16s
722: learn: 0.2662356 total: 38.9s remaining: 16s
723: learn: 0.2661975 total: 39s remaining: 15.9s
724: learn: 0.2660475 total: 39s remaining: 15.9s
725: learn: 0.2659599 total: 39.1s remaining: 15.8s
726: learn: 0.2658815 total: 39.1s remaining: 15.8s
727: learn: 0.2657779 total: 39.2s remaining: 15.7s
728: learn: 0.2657211 total: 39.2s remaining: 15.7s
729: learn: 0.2657053 total: 39.3s remaining: 15.6s
730: learn: 0.2655881 total: 39.3s remaining: 15.5s
731: learn: 0.2655466 total: 39.4s remaining: 15.5s
732: learn: 0.2655027 total: 39.4s remaining: 15.4s
733: learn: 0.2653731 total: 39.5s remaining: 15.4s
734: learn: 0.2653256 total: 39.5s remaining: 15.3s
735: learn: 0.2652896 total: 39.6s remaining: 15.3s
736: learn: 0.2652736 total: 39.6s remaining: 15.2s
737: learn: 0.2652735 total: 39.6s remaining: 15.1s
738: learn: 0.2652734 total: 39.7s remaining: 15.1s
739: learn: 0.2651813 total: 39.7s remaining: 15s
740: learn: 0.2651732 total: 39.8s remaining: 15s
741: learn: 0.2650485 total: 39.8s remaining: 14.9s
742: learn: 0.2649428 total: 39.9s remaining: 14.9s
743: learn: 0.2649025 total: 39.9s remaining: 14.8s
744: learn: 0.2648162 total: 40s remaining: 14.8s
745: learn: 0.2647418 total: 40s remaining: 14.7s
746: learn: 0.2647293 total: 40.1s remaining: 14.7s
747: learn: 0.2646700 total: 40.1s remaining: 14.6s
748: learn: 0.2646156 total: 40.2s remaining: 14.5s
749: learn: 0.2645754 total: 40.2s remaining: 14.5s
750: learn: 0.2645241 total: 40.3s remaining: 14.4s
751: learn: 0.2644279 total: 40.3s remaining: 14.4s
752: learn: 0.2643840 total: 40.4s remaining: 14.3s
753: learn: 0.2643308 total: 40.4s remaining: 14.3s
754: learn: 0.2642815 total: 40.5s remaining: 14.2s
755: learn: 0.2641335 total: 40.5s remaining: 14.2s
756: learn: 0.2641247 total: 40.6s remaining: 14.1s
757: learn: 0.2640704 total: 40.6s remaining: 14.1s
758: learn: 0.2640704 total: 40.7s remaining: 14s
759: learn: 0.2640195 total: 40.7s remaining: 13.9s
760: learn: 0.2640154 total: 40.8s remaining: 13.9s
761: learn: 0.2639636 total: 40.8s remaining: 13.8s
762: learn: 0.2639395 total: 40.9s remaining: 13.8s
763: learn: 0.2638558 total: 40.9s remaining: 13.7s
764: learn: 0.2638556 total: 40.9s remaining: 13.6s
765: learn: 0.2638551 total: 41s remaining: 13.6s
766: learn: 0.2636189 total: 41s remaining: 13.5s
767: learn: 0.2635377 total: 41.1s remaining: 13.5s
768: learn: 0.2634377 total: 41.1s remaining: 13.4s
769: learn: 0.2634032 total: 41.2s remaining: 13.4s
770: learn: 0.2633799 total: 41.2s remaining: 13.3s
771: learn: 0.2631466 total: 41.3s remaining: 13.3s
772: learn: 0.2630756 total: 41.3s remaining: 13.2s
773: learn: 0.2630477 total: 41.4s remaining: 13.1s
774: learn: 0.2630238 total: 41.4s remaining: 13.1s
775: learn: 0.2630234 total: 41.4s remaining: 13s
776: learn: 0.2629925 total: 41.5s remaining: 13s
777: learn: 0.2629922 total: 41.5s remaining: 12.9s
778: learn: 0.2629335 total: 41.6s remaining: 12.9s
779: learn: 0.2629160 total: 41.6s remaining: 12.8s
780: learn: 0.2628871 total: 41.7s remaining: 12.8s
781: learn: 0.2628171 total: 41.7s remaining: 12.7s
782: learn: 0.2627856 total: 41.8s remaining: 12.6s
783: learn: 0.2627855 total: 41.8s remaining: 12.6s
784: learn: 0.2626694 total: 41.9s remaining: 12.5s
785: learn: 0.2626314 total: 41.9s remaining: 12.5s
786: learn: 0.2625790 total: 41.9s remaining: 12.4s
787: learn: 0.2624470 total: 42s remaining: 12.4s
788: learn: 0.2624047 total: 42.1s remaining: 12.3s
789: learn: 0.2624046 total: 42.1s remaining: 12.3s
790: learn: 0.2623366 total: 42.1s remaining: 12.2s
791: learn: 0.2623214 total: 42.2s remaining: 12.1s
792: learn: 0.2622424 total: 42.2s remaining: 12.1s
793: learn: 0.2622420 total: 42.3s remaining: 12s
794: learn: 0.2621679 total: 42.3s remaining: 12s
795: learn: 0.2620849 total: 42.4s remaining: 11.9s
796: learn: 0.2619969 total: 42.4s remaining: 11.9s
797: learn: 0.2618774 total: 42.5s remaining: 11.8s
798: learn: 0.2618159 total: 42.5s remaining: 11.8s
799: learn: 0.2616985 total: 42.6s remaining: 11.7s
800: learn: 0.2616727 total: 42.6s remaining: 11.6s
801: learn: 0.2616032 total: 42.7s remaining: 11.6s
802: learn: 0.2615703 total: 42.7s remaining: 11.5s
803: learn: 0.2614134 total: 42.8s remaining: 11.5s
804: learn: 0.2613408 total: 42.8s remaining: 11.4s
805: learn: 0.2613175 total: 42.8s remaining: 11.4s
806: learn: 0.2612249 total: 42.9s remaining: 11.3s
807: learn: 0.2612015 total: 42.9s remaining: 11.3s
808: learn: 0.2611345 total: 43s remaining: 11.2s
809: learn: 0.2611146 total: 43s remaining: 11.2s
810: learn: 0.2610883 total: 43.1s remaining: 11.1s
811: learn: 0.2610357 total: 43.1s remaining: 11.1s
812: learn: 0.2610007 total: 43.2s remaining: 11s
813: learn: 0.2609033 total: 43.2s remaining: 10.9s
814: learn: 0.2608492 total: 43.3s remaining: 10.9s
815: learn: 0.2607992 total: 43.3s remaining: 10.8s
816: learn: 0.2607757 total: 43.4s remaining: 10.8s
817: learn: 0.2606783 total: 43.4s remaining: 10.7s
818: learn: 0.2606714 total: 43.5s remaining: 10.7s
819: learn: 0.2605726 total: 43.5s remaining: 10.6s
820: learn: 0.2605514 total: 43.6s remaining: 10.6s
821: learn: 0.2605244 total: 43.6s remaining: 10.5s
822: learn: 0.2604728 total: 43.7s remaining: 10.5s
823: learn: 0.2603861 total: 43.7s remaining: 10.4s
824: learn: 0.2603861 total: 43.8s remaining: 10.3s
825: learn: 0.2603805 total: 43.8s remaining: 10.3s
826: learn: 0.2603788 total: 43.9s remaining: 10.2s
827: learn: 0.2603093 total: 43.9s remaining: 10.2s
828: learn: 0.2602531 total: 44s remaining: 10.1s
829: learn: 0.2601963 total: 44s remaining: 10.1s
830: learn: 0.2601789 total: 44.1s remaining: 10s
831: learn: 0.2600810 total: 44.1s remaining: 9.97s
832: learn: 0.2600148 total: 44.2s remaining: 9.91s
833: learn: 0.2599941 total: 44.2s remaining: 9.86s
834: learn: 0.2599401 total: 44.3s remaining: 9.81s
835: learn: 0.2598456 total: 44.3s remaining: 9.75s
836: learn: 0.2598456 total: 44.3s remaining: 9.69s
837: learn: 0.2598021 total: 44.4s remaining: 9.64s
838: learn: 0.2597819 total: 44.4s remaining: 9.59s
839: learn: 0.2597684 total: 44.5s remaining: 9.53s
840: learn: 0.2597076 total: 44.5s remaining: 9.48s
841: learn: 0.2596675 total: 44.6s remaining: 9.42s
842: learn: 0.2596252 total: 44.6s remaining: 9.37s
843: learn: 0.2595861 total: 44.7s remaining: 9.32s
844: learn: 0.2595624 total: 44.7s remaining: 9.26s
845: learn: 0.2595287 total: 44.8s remaining: 9.21s
846: learn: 0.2594833 total: 44.8s remaining: 9.15s
847: learn: 0.2594510 total: 44.9s remaining: 9.1s
848: learn: 0.2594301 total: 44.9s remaining: 9.05s
849: learn: 0.2593358 total: 45s remaining: 8.99s
850: learn: 0.2592944 total: 45s remaining: 8.94s
851: learn: 0.2592764 total: 45.1s remaining: 8.89s
852: learn: 0.2592757 total: 45.1s remaining: 8.83s
853: learn: 0.2592248 total: 45.2s remaining: 8.78s
854: learn: 0.2592248 total: 45.2s remaining: 8.72s
855: learn: 0.2591416 total: 45.2s remaining: 8.67s
856: learn: 0.2590379 total: 45.3s remaining: 8.61s
857: learn: 0.2589164 total: 45.3s remaining: 8.56s
858: learn: 0.2588576 total: 45.4s remaining: 8.51s
859: learn: 0.2588313 total: 45.4s remaining: 8.45s
860: learn: 0.2588041 total: 45.5s remaining: 8.4s
861: learn: 0.2587929 total: 45.5s remaining: 8.35s
862: learn: 0.2587339 total: 45.6s remaining: 8.29s
863: learn: 0.2587011 total: 45.6s remaining: 8.24s
864: learn: 0.2586865 total: 45.7s remaining: 8.19s
865: learn: 0.2586283 total: 45.7s remaining: 8.13s
866: learn: 0.2585699 total: 45.8s remaining: 8.08s
867: learn: 0.2584818 total: 45.8s remaining: 8.03s
868: learn: 0.2584667 total: 45.9s remaining: 7.97s
869: learn: 0.2584263 total: 45.9s remaining: 7.92s
870: learn: 0.2583981 total: 46s remaining: 7.87s
871: learn: 0.2583707 total: 46s remaining: 7.81s
872: learn: 0.2582703 total: 46.1s remaining: 7.76s
873: learn: 0.2582003 total: 46.1s remaining: 7.71s
874: learn: 0.2581266 total: 46.2s remaining: 7.65s
875: learn: 0.2580845 total: 46.2s remaining: 7.6s
876: learn: 0.2580583 total: 46.3s remaining: 7.54s
877: learn: 0.2580410 total: 46.3s remaining: 7.49s
878: learn: 0.2579656 total: 46.4s remaining: 7.44s
879: learn: 0.2578975 total: 46.4s remaining: 7.39s
880: learn: 0.2578944 total: 46.5s remaining: 7.33s
881: learn: 0.2577710 total: 46.5s remaining: 7.28s
882: learn: 0.2577618 total: 46.6s remaining: 7.23s
883: learn: 0.2577613 total: 46.6s remaining: 7.17s
884: learn: 0.2576812 total: 46.7s remaining: 7.12s
885: learn: 0.2576558 total: 46.7s remaining: 7.06s
886: learn: 0.2575359 total: 46.8s remaining: 7.01s
887: learn: 0.2575253 total: 46.8s remaining: 6.96s
888: learn: 0.2574128 total: 46.9s remaining: 6.91s
889: learn: 0.2573802 total: 46.9s remaining: 6.85s
890: learn: 0.2573344 total: 47s remaining: 6.8s
891: learn: 0.2573250 total: 47s remaining: 6.75s
892: learn: 0.2572540 total: 47.1s remaining: 6.69s
893: learn: 0.2571576 total: 47.1s remaining: 6.64s
894: learn: 0.2571067 total: 47.2s remaining: 6.59s
895: learn: 0.2570939 total: 47.2s remaining: 6.53s
896: learn: 0.2569321 total: 47.3s remaining: 6.48s
897: learn: 0.2568685 total: 47.3s remaining: 6.43s
898: learn: 0.2568219 total: 47.4s remaining: 6.37s
899: learn: 0.2567601 total: 47.4s remaining: 6.32s
900: learn: 0.2566539 total: 47.5s remaining: 6.27s
901: learn: 0.2566288 total: 47.5s remaining: 6.22s
902: learn: 0.2566286 total: 47.5s remaining: 6.16s
903: learn: 0.2565540 total: 47.6s remaining: 6.11s
904: learn: 0.2565534 total: 47.6s remaining: 6.05s
905: learn: 0.2565487 total: 47.7s remaining: 6s
906: learn: 0.2564957 total: 47.7s remaining: 5.95s
907: learn: 0.2564578 total: 47.8s remaining: 5.9s
908: learn: 0.2562753 total: 47.8s remaining: 5.84s
909: learn: 0.2562747 total: 47.9s remaining: 5.79s
910: learn: 0.2562338 total: 47.9s remaining: 5.74s
911: learn: 0.2562318 total: 48s remaining: 5.68s
912: learn: 0.2560812 total: 48s remaining: 5.63s
913: learn: 0.2560729 total: 48.1s remaining: 5.58s
914: learn: 0.2559909 total: 48.1s remaining: 5.52s
915: learn: 0.2559619 total: 48.2s remaining: 5.47s
916: learn: 0.2559182 total: 48.2s remaining: 5.42s
917: learn: 0.2557319 total: 48.3s remaining: 5.36s
918: learn: 0.2557191 total: 48.3s remaining: 5.31s
919: learn: 0.2556548 total: 48.4s remaining: 5.26s
920: learn: 0.2556323 total: 48.4s remaining: 5.21s
921: learn: 0.2555172 total: 48.5s remaining: 5.15s
922: learn: 0.2554692 total: 48.5s remaining: 5.1s
923: learn: 0.2554113 total: 48.6s remaining: 5.05s
924: learn: 0.2553945 total: 48.6s remaining: 5s
925: learn: 0.2553340 total: 48.7s remaining: 4.94s
926: learn: 0.2553318 total: 48.7s remaining: 4.89s
927: learn: 0.2552770 total: 48.8s remaining: 4.84s
928: learn: 0.2552305 total: 48.8s remaining: 4.78s
929: learn: 0.2551752 total: 48.9s remaining: 4.73s
930: learn: 0.2551667 total: 48.9s remaining: 4.68s
931: learn: 0.2551639 total: 49s remaining: 4.63s
932: learn: 0.2551637 total: 49s remaining: 4.57s
933: learn: 0.2551631 total: 49.1s remaining: 4.52s
934: learn: 0.2551117 total: 49.1s remaining: 4.46s
935: learn: 0.2551068 total: 49.2s remaining: 4.41s
936: learn: 0.2550917 total: 49.2s remaining: 4.36s
937: learn: 0.2550437 total: 49.3s remaining: 4.31s
938: learn: 0.2549349 total: 49.4s remaining: 4.26s
939: learn: 0.2548053 total: 49.4s remaining: 4.21s
940: learn: 0.2548052 total: 49.4s remaining: 4.15s
941: learn: 0.2547737 total: 49.5s remaining: 4.1s
942: learn: 0.2547483 total: 49.6s remaining: 4.05s
943: learn: 0.2547474 total: 49.6s remaining: 4s
944: learn: 0.2547463 total: 49.7s remaining: 3.94s
945: learn: 0.2547315 total: 49.8s remaining: 3.89s
946: learn: 0.2547224 total: 49.8s remaining: 3.84s
947: learn: 0.2547220 total: 49.8s remaining: 3.79s
948: learn: 0.2546552 total: 49.9s remaining: 3.73s
949: learn: 0.2546392 total: 50s remaining: 3.68s
950: learn: 0.2546386 total: 50s remaining: 3.63s
951: learn: 0.2544578 total: 50.1s remaining: 3.58s
952: learn: 0.2544085 total: 50.1s remaining: 3.52s
953: learn: 0.2543340 total: 50.2s remaining: 3.47s
954: learn: 0.2543016 total: 50.2s remaining: 3.42s
955: learn: 0.2543015 total: 50.3s remaining: 3.37s
956: learn: 0.2543014 total: 50.3s remaining: 3.31s
957: learn: 0.2542572 total: 50.4s remaining: 3.26s
958: learn: 0.2542535 total: 50.4s remaining: 3.21s
959: learn: 0.2540336 total: 50.5s remaining: 3.15s
960: learn: 0.2539736 total: 50.6s remaining: 3.1s
961: learn: 0.2539653 total: 50.6s remaining: 3.05s
962: learn: 0.2539187 total: 50.7s remaining: 3s
963: learn: 0.2537790 total: 50.7s remaining: 2.95s
964: learn: 0.2537401 total: 50.8s remaining: 2.9s
965: learn: 0.2537317 total: 50.9s remaining: 2.84s
966: learn: 0.2537315 total: 50.9s remaining: 2.79s
967: learn: 0.2537315 total: 50.9s remaining: 2.74s
968: learn: 0.2536145 total: 51s remaining: 2.68s
969: learn: 0.2535526 total: 51.1s remaining: 2.63s
970: learn: 0.2535194 total: 51.1s remaining: 2.58s
971: learn: 0.2535194 total: 51.1s remaining: 2.52s
972: learn: 0.2534902 total: 51.2s remaining: 2.47s
973: learn: 0.2534430 total: 51.3s remaining: 2.42s
974: learn: 0.2533826 total: 51.3s remaining: 2.37s
975: learn: 0.2532672 total: 51.4s remaining: 2.32s
976: learn: 0.2532042 total: 51.5s remaining: 2.26s
977: learn: 0.2531440 total: 51.5s remaining: 2.21s
978: learn: 0.2530694 total: 51.6s remaining: 2.16s
979: learn: 0.2530438 total: 51.6s remaining: 2.11s
980: learn: 0.2530281 total: 51.7s remaining: 2.06s
981: learn: 0.2529865 total: 51.8s remaining: 2s
982: learn: 0.2529863 total: 51.8s remaining: 1.95s
983: learn: 0.2529589 total: 51.9s remaining: 1.9s
984: learn: 0.2529202 total: 51.9s remaining: 1.84s
985: learn: 0.2528667 total: 52s remaining: 1.79s
986: learn: 0.2527533 total: 52.1s remaining: 1.74s
987: learn: 0.2527471 total: 52.1s remaining: 1.69s
988: learn: 0.2527259 total: 52.2s remaining: 1.64s
989: learn: 0.2526566 total: 52.2s remaining: 1.58s
990: learn: 0.2525686 total: 52.3s remaining: 1.53s
991: learn: 0.2525683 total: 52.4s remaining: 1.48s
992: learn: 0.2525476 total: 52.4s remaining: 1.43s
993: learn: 0.2524674 total: 52.5s remaining: 1.37s
994: learn: 0.2524521 total: 52.6s remaining: 1.32s
995: learn: 0.2524427 total: 52.6s remaining: 1.27s
996: learn: 0.2524168 total: 52.7s remaining: 1.21s
997: learn: 0.2524166 total: 52.7s remaining: 1.16s
998: learn: 0.2523150 total: 52.8s remaining: 1.11s
999: learn: 0.2523125 total: 52.8s remaining: 1.06s
1000: learn: 0.2522751 total: 52.9s remaining: 1s
1001: learn: 0.2522050 total: 52.9s remaining: 951ms
1002: learn: 0.2522050 total: 52.9s remaining: 897ms
1003: learn: 0.2521778 total: 53s remaining: 845ms
1004: learn: 0.2521778 total: 53s remaining: 791ms
1005: learn: 0.2521777 total: 53s remaining: 738ms
1006: learn: 0.2521773 total: 53.1s remaining: 685ms
1007: learn: 0.2520853 total: 53.1s remaining: 633ms
1008: learn: 0.2519614 total: 53.2s remaining: 580ms
1009: learn: 0.2519463 total: 53.3s remaining: 527ms
1010: learn: 0.2518657 total: 53.3s remaining: 475ms
1011: learn: 0.2518163 total: 53.4s remaining: 422ms
1012: learn: 0.2517339 total: 53.4s remaining: 369ms
1013: learn: 0.2516194 total: 53.5s remaining: 316ms
1014: learn: 0.2515742 total: 53.5s remaining: 264ms
1015: learn: 0.2514941 total: 53.6s remaining: 211ms
1016: learn: 0.2514775 total: 53.6s remaining: 158ms
1017: learn: 0.2514766 total: 53.7s remaining: 105ms
1018: learn: 0.2514735 total: 53.7s remaining: 52.7ms
1019: learn: 0.2514643 total: 53.8s remaining: 0us
Finished training fold 0 - running score 0.8616615853658537
Running fold 1, 15735 train samples, 2624 validation samples
0: learn: 0.6486449 total: 53.3ms remaining: 54.3s
1: learn: 0.6110008 total: 110ms remaining: 56.2s
2: learn: 0.5776957 total: 159ms remaining: 53.9s
3: learn: 0.5487934 total: 210ms remaining: 53.4s
4: learn: 0.5241085 total: 259ms remaining: 52.5s
5: learn: 0.5027436 total: 311ms remaining: 52.6s
6: learn: 0.4845312 total: 360ms remaining: 52.1s
7: learn: 0.4686219 total: 411ms remaining: 52.1s
8: learn: 0.4550987 total: 468ms remaining: 52.5s
9: learn: 0.4432718 total: 529ms remaining: 53.4s
10: learn: 0.4331384 total: 583ms remaining: 53.4s
11: learn: 0.4242779 total: 641ms remaining: 53.8s
12: learn: 0.4167812 total: 698ms remaining: 54s
13: learn: 0.4102541 total: 749ms remaining: 53.8s
14: learn: 0.4044243 total: 801ms remaining: 53.7s
15: learn: 0.3995755 total: 850ms remaining: 53.3s
16: learn: 0.3952210 total: 899ms remaining: 53.1s
17: learn: 0.3913713 total: 952ms remaining: 53s
18: learn: 0.3880010 total: 1s remaining: 52.8s
19: learn: 0.3851482 total: 1.05s remaining: 52.8s
20: learn: 0.3825566 total: 1.11s remaining: 52.7s
21: learn: 0.3802600 total: 1.16s remaining: 52.6s
22: learn: 0.3783038 total: 1.21s remaining: 52.6s
23: learn: 0.3765507 total: 1.26s remaining: 52.4s
24: learn: 0.3750694 total: 1.31s remaining: 52.3s
25: learn: 0.3738243 total: 1.37s remaining: 52.4s
26: learn: 0.3727281 total: 1.42s remaining: 52.3s
27: learn: 0.3717045 total: 1.47s remaining: 52.2s
28: learn: 0.3707401 total: 1.52s remaining: 52.1s
29: learn: 0.3699103 total: 1.58s remaining: 52.2s
30: learn: 0.3691843 total: 1.63s remaining: 52.1s
31: learn: 0.3683938 total: 1.68s remaining: 52s
32: learn: 0.3678135 total: 1.73s remaining: 51.9s
33: learn: 0.3672537 total: 1.79s remaining: 51.8s
34: learn: 0.3666811 total: 1.84s remaining: 51.7s
35: learn: 0.3660565 total: 1.89s remaining: 51.7s
36: learn: 0.3657858 total: 1.91s remaining: 50.8s
37: learn: 0.3652087 total: 1.97s remaining: 50.9s
38: learn: 0.3648310 total: 2.03s remaining: 51.1s
39: learn: 0.3644896 total: 2.08s remaining: 51s
40: learn: 0.3641104 total: 2.13s remaining: 50.9s
41: learn: 0.3638511 total: 2.19s remaining: 50.9s
42: learn: 0.3635131 total: 2.24s remaining: 50.9s
43: learn: 0.3630642 total: 2.3s remaining: 51s
44: learn: 0.3625916 total: 2.36s remaining: 51.1s
45: learn: 0.3621347 total: 2.42s remaining: 51.2s
46: learn: 0.3616561 total: 2.47s remaining: 51.2s
47: learn: 0.3613344 total: 2.53s remaining: 51.3s
48: learn: 0.3611623 total: 2.59s remaining: 51.3s
49: learn: 0.3608931 total: 2.64s remaining: 51.2s
50: learn: 0.3604003 total: 2.69s remaining: 51.1s
51: learn: 0.3601623 total: 2.74s remaining: 51s
52: learn: 0.3598896 total: 2.79s remaining: 50.9s
53: learn: 0.3596340 total: 2.84s remaining: 50.8s
54: learn: 0.3594198 total: 2.89s remaining: 50.7s
55: learn: 0.3592348 total: 2.94s remaining: 50.6s
56: learn: 0.3588743 total: 2.99s remaining: 50.5s
57: learn: 0.3586804 total: 3.04s remaining: 50.4s
58: learn: 0.3582899 total: 3.1s remaining: 50.4s
59: learn: 0.3581564 total: 3.15s remaining: 50.4s
60: learn: 0.3579580 total: 3.2s remaining: 50.3s
61: learn: 0.3577063 total: 3.25s remaining: 50.2s
62: learn: 0.3575007 total: 3.3s remaining: 50.1s
63: learn: 0.3573177 total: 3.36s remaining: 50.2s
64: learn: 0.3569349 total: 3.43s remaining: 50.4s
65: learn: 0.3567656 total: 3.51s remaining: 50.7s
66: learn: 0.3565227 total: 3.58s remaining: 51s
67: learn: 0.3564139 total: 3.65s remaining: 51.2s
68: learn: 0.3562318 total: 3.72s remaining: 51.2s
69: learn: 0.3560526 total: 3.78s remaining: 51.3s
70: learn: 0.3558882 total: 3.84s remaining: 51.4s
71: learn: 0.3556686 total: 3.9s remaining: 51.4s
72: learn: 0.3554702 total: 3.98s remaining: 51.6s
73: learn: 0.3552654 total: 4.05s remaining: 51.7s
74: learn: 0.3550957 total: 4.12s remaining: 51.9s
75: learn: 0.3549876 total: 4.18s remaining: 52s
76: learn: 0.3545496 total: 4.25s remaining: 52.1s
77: learn: 0.3542049 total: 4.32s remaining: 52.1s
78: learn: 0.3539054 total: 4.38s remaining: 52.2s
79: learn: 0.3536600 total: 4.45s remaining: 52.3s
80: learn: 0.3533479 total: 4.52s remaining: 52.4s
81: learn: 0.3530731 total: 4.58s remaining: 52.4s
82: learn: 0.3528344 total: 4.64s remaining: 52.4s
83: learn: 0.3525625 total: 4.71s remaining: 52.5s
84: learn: 0.3522102 total: 4.78s remaining: 52.5s
85: learn: 0.3521289 total: 4.84s remaining: 52.6s
86: learn: 0.3519072 total: 4.91s remaining: 52.7s
87: learn: 0.3516930 total: 4.98s remaining: 52.8s
88: learn: 0.3515411 total: 5.05s remaining: 52.8s
89: learn: 0.3513060 total: 5.12s remaining: 52.9s
90: learn: 0.3511216 total: 5.2s remaining: 53s
91: learn: 0.3509246 total: 5.27s remaining: 53.1s
92: learn: 0.3504499 total: 5.34s remaining: 53.2s
93: learn: 0.3503694 total: 5.4s remaining: 53.2s
94: learn: 0.3501770 total: 5.46s remaining: 53.2s
95: learn: 0.3498937 total: 5.52s remaining: 53.2s
96: learn: 0.3495112 total: 5.59s remaining: 53.2s
97: learn: 0.3492977 total: 5.65s remaining: 53.1s
98: learn: 0.3491640 total: 5.71s remaining: 53.1s
99: learn: 0.3488566 total: 5.79s remaining: 53.2s
100: learn: 0.3487467 total: 5.86s remaining: 53.3s
101: learn: 0.3483938 total: 5.94s remaining: 53.4s
102: learn: 0.3482012 total: 6.01s remaining: 53.5s
103: learn: 0.3480828 total: 6.08s remaining: 53.5s
104: learn: 0.3479604 total: 6.14s remaining: 53.5s
105: learn: 0.3476520 total: 6.21s remaining: 53.6s
106: learn: 0.3474388 total: 6.28s remaining: 53.6s
107: learn: 0.3471969 total: 6.34s remaining: 53.5s
108: learn: 0.3469173 total: 6.4s remaining: 53.5s
109: learn: 0.3467255 total: 6.46s remaining: 53.4s
110: learn: 0.3465647 total: 6.52s remaining: 53.4s
111: learn: 0.3464117 total: 6.58s remaining: 53.3s
112: learn: 0.3461852 total: 6.64s remaining: 53.3s
113: learn: 0.3459337 total: 6.7s remaining: 53.2s
114: learn: 0.3457812 total: 6.76s remaining: 53.2s
115: learn: 0.3456492 total: 6.82s remaining: 53.2s
116: learn: 0.3455249 total: 6.88s remaining: 53.1s
117: learn: 0.3453753 total: 6.94s remaining: 53s
118: learn: 0.3452522 total: 7s remaining: 53s
119: learn: 0.3450823 total: 7.06s remaining: 53s
120: learn: 0.3448010 total: 7.12s remaining: 52.9s
121: learn: 0.3444884 total: 7.17s remaining: 52.8s
122: learn: 0.3443791 total: 7.24s remaining: 52.8s
123: learn: 0.3441473 total: 7.3s remaining: 52.8s
124: learn: 0.3438636 total: 7.35s remaining: 52.7s
125: learn: 0.3436192 total: 7.4s remaining: 52.5s
126: learn: 0.3434228 total: 7.45s remaining: 52.4s
127: learn: 0.3432857 total: 7.5s remaining: 52.3s
128: learn: 0.3432158 total: 7.55s remaining: 52.1s
129: learn: 0.3430014 total: 7.61s remaining: 52.1s
130: learn: 0.3428204 total: 7.67s remaining: 52s
131: learn: 0.3426693 total: 7.72s remaining: 51.9s
132: learn: 0.3424168 total: 7.78s remaining: 51.9s
133: learn: 0.3422316 total: 7.84s remaining: 51.8s
134: learn: 0.3420881 total: 7.89s remaining: 51.8s
135: learn: 0.3419177 total: 7.95s remaining: 51.7s
136: learn: 0.3417360 total: 8.01s remaining: 51.6s
137: learn: 0.3416390 total: 8.06s remaining: 51.5s
138: learn: 0.3416225 total: 8.08s remaining: 51.2s
139: learn: 0.3414304 total: 8.13s remaining: 51.1s
140: learn: 0.3412572 total: 8.18s remaining: 51s
141: learn: 0.3410196 total: 8.23s remaining: 50.9s
142: learn: 0.3407609 total: 8.29s remaining: 50.8s
143: learn: 0.3406182 total: 8.34s remaining: 50.7s
144: learn: 0.3404296 total: 8.39s remaining: 50.6s
145: learn: 0.3402349 total: 8.43s remaining: 50.5s
146: learn: 0.3399339 total: 8.49s remaining: 50.4s
147: learn: 0.3397228 total: 8.54s remaining: 50.3s
148: learn: 0.3393079 total: 8.59s remaining: 50.2s
149: learn: 0.3390502 total: 8.64s remaining: 50.1s
150: learn: 0.3388721 total: 8.69s remaining: 50s
151: learn: 0.3385359 total: 8.74s remaining: 49.9s
152: learn: 0.3383316 total: 8.79s remaining: 49.8s
153: learn: 0.3381479 total: 8.84s remaining: 49.7s
154: learn: 0.3379248 total: 8.89s remaining: 49.6s
155: learn: 0.3377860 total: 8.94s remaining: 49.5s
156: learn: 0.3376264 total: 8.99s remaining: 49.4s
157: learn: 0.3373898 total: 9.04s remaining: 49.3s
158: learn: 0.3372318 total: 9.1s remaining: 49.3s
159: learn: 0.3368361 total: 9.14s remaining: 49.2s
160: learn: 0.3366511 total: 9.21s remaining: 49.1s
161: learn: 0.3364913 total: 9.26s remaining: 49.1s
162: learn: 0.3363162 total: 9.33s remaining: 49s
163: learn: 0.3361831 total: 9.38s remaining: 49s
164: learn: 0.3360592 total: 9.44s remaining: 48.9s
165: learn: 0.3358980 total: 9.5s remaining: 48.9s
166: learn: 0.3356709 total: 9.55s remaining: 48.8s
167: learn: 0.3355505 total: 9.61s remaining: 48.7s
168: learn: 0.3352518 total: 9.67s remaining: 48.7s
169: learn: 0.3350063 total: 9.72s remaining: 48.6s
170: learn: 0.3348308 total: 9.77s remaining: 48.5s
171: learn: 0.3345668 total: 9.82s remaining: 48.4s
172: learn: 0.3344363 total: 9.88s remaining: 48.4s
173: learn: 0.3342799 total: 9.94s remaining: 48.3s
174: learn: 0.3338929 total: 10s remaining: 48.3s
175: learn: 0.3336215 total: 10.1s remaining: 48.2s
176: learn: 0.3335063 total: 10.1s remaining: 48.1s
177: learn: 0.3333082 total: 10.2s remaining: 48.1s
178: learn: 0.3331897 total: 10.2s remaining: 48s
179: learn: 0.3330050 total: 10.3s remaining: 48s
180: learn: 0.3326789 total: 10.4s remaining: 48s
181: learn: 0.3323792 total: 10.4s remaining: 48s
182: learn: 0.3321994 total: 10.5s remaining: 48s
183: learn: 0.3320735 total: 10.5s remaining: 47.9s
184: learn: 0.3318392 total: 10.6s remaining: 47.9s
185: learn: 0.3315927 total: 10.7s remaining: 47.8s
186: learn: 0.3314218 total: 10.7s remaining: 47.8s
187: learn: 0.3310393 total: 10.8s remaining: 47.8s
188: learn: 0.3307985 total: 10.9s remaining: 47.7s
189: learn: 0.3304568 total: 10.9s remaining: 47.7s
190: learn: 0.3302922 total: 11s remaining: 47.7s
191: learn: 0.3300245 total: 11s remaining: 47.6s
192: learn: 0.3299017 total: 11.1s remaining: 47.6s
193: learn: 0.3297460 total: 11.2s remaining: 47.5s
194: learn: 0.3296458 total: 11.2s remaining: 47.5s
195: learn: 0.3293675 total: 11.3s remaining: 47.5s
196: learn: 0.3291265 total: 11.4s remaining: 47.5s
197: learn: 0.3289127 total: 11.4s remaining: 47.4s
198: learn: 0.3288133 total: 11.5s remaining: 47.4s
199: learn: 0.3284137 total: 11.6s remaining: 47.4s
200: learn: 0.3281156 total: 11.6s remaining: 47.4s
201: learn: 0.3278330 total: 11.7s remaining: 47.4s
202: learn: 0.3277114 total: 11.8s remaining: 47.4s
203: learn: 0.3272461 total: 11.9s remaining: 47.4s
204: learn: 0.3267705 total: 11.9s remaining: 47.4s
205: learn: 0.3265917 total: 12s remaining: 47.4s
206: learn: 0.3264030 total: 12.1s remaining: 47.4s
207: learn: 0.3262831 total: 12.1s remaining: 47.4s
208: learn: 0.3260558 total: 12.2s remaining: 47.4s
209: learn: 0.3258209 total: 12.3s remaining: 47.4s
210: learn: 0.3256968 total: 12.4s remaining: 47.4s
211: learn: 0.3256117 total: 12.4s remaining: 47.4s
212: learn: 0.3254280 total: 12.5s remaining: 47.3s
213: learn: 0.3252005 total: 12.6s remaining: 47.3s
214: learn: 0.3250563 total: 12.6s remaining: 47.3s
215: learn: 0.3248665 total: 12.7s remaining: 47.3s
216: learn: 0.3247367 total: 12.8s remaining: 47.3s
217: learn: 0.3246288 total: 12.8s remaining: 47.3s
218: learn: 0.3244931 total: 12.9s remaining: 47.2s
219: learn: 0.3243829 total: 13s remaining: 47.2s
220: learn: 0.3242944 total: 13.1s remaining: 47.2s
221: learn: 0.3239221 total: 13.1s remaining: 47.2s
222: learn: 0.3236629 total: 13.2s remaining: 47.1s
223: learn: 0.3235495 total: 13.3s remaining: 47.1s
224: learn: 0.3232583 total: 13.3s remaining: 47.1s
225: learn: 0.3229722 total: 13.4s remaining: 47.1s
226: learn: 0.3227289 total: 13.5s remaining: 47.1s
227: learn: 0.3225482 total: 13.6s remaining: 47.1s
228: learn: 0.3224196 total: 13.6s remaining: 47s
229: learn: 0.3222854 total: 13.7s remaining: 46.9s
230: learn: 0.3221282 total: 13.7s remaining: 46.9s
231: learn: 0.3219369 total: 13.8s remaining: 46.8s
232: learn: 0.3216804 total: 13.8s remaining: 46.7s
233: learn: 0.3216119 total: 13.9s remaining: 46.7s
234: learn: 0.3214845 total: 13.9s remaining: 46.6s
235: learn: 0.3213036 total: 14s remaining: 46.5s
236: learn: 0.3211943 total: 14s remaining: 46.4s
237: learn: 0.3210443 total: 14.1s remaining: 46.4s
238: learn: 0.3208794 total: 14.2s remaining: 46.3s
239: learn: 0.3207515 total: 14.2s remaining: 46.2s
240: learn: 0.3206115 total: 14.3s remaining: 46.2s
241: learn: 0.3203486 total: 14.4s remaining: 46.3s
242: learn: 0.3201841 total: 14.5s remaining: 46.2s
243: learn: 0.3199323 total: 14.5s remaining: 46.2s
244: learn: 0.3196782 total: 14.6s remaining: 46.1s
245: learn: 0.3194930 total: 14.6s remaining: 46s
246: learn: 0.3193112 total: 14.7s remaining: 45.9s
247: learn: 0.3191032 total: 14.7s remaining: 45.8s
248: learn: 0.3187700 total: 14.8s remaining: 45.8s
249: learn: 0.3186070 total: 14.8s remaining: 45.7s
250: learn: 0.3184932 total: 14.9s remaining: 45.6s
251: learn: 0.3182387 total: 14.9s remaining: 45.5s
252: learn: 0.3181320 total: 15s remaining: 45.4s
253: learn: 0.3179208 total: 15s remaining: 45.4s
254: learn: 0.3177568 total: 15.1s remaining: 45.3s
255: learn: 0.3174356 total: 15.1s remaining: 45.2s
256: learn: 0.3173493 total: 15.2s remaining: 45.1s
257: learn: 0.3171460 total: 15.3s remaining: 45s
258: learn: 0.3169996 total: 15.3s remaining: 45s
259: learn: 0.3168511 total: 15.4s remaining: 44.9s
260: learn: 0.3166329 total: 15.4s remaining: 44.8s
261: learn: 0.3163478 total: 15.5s remaining: 44.7s
262: learn: 0.3160592 total: 15.5s remaining: 44.6s
263: learn: 0.3158390 total: 15.6s remaining: 44.6s
264: learn: 0.3157322 total: 15.6s remaining: 44.5s
265: learn: 0.3154858 total: 15.7s remaining: 44.4s
266: learn: 0.3152950 total: 15.7s remaining: 44.4s
267: learn: 0.3150677 total: 15.8s remaining: 44.3s
268: learn: 0.3149255 total: 15.8s remaining: 44.2s
269: learn: 0.3146191 total: 15.9s remaining: 44.2s
270: learn: 0.3144203 total: 16s remaining: 44.1s
271: learn: 0.3142498 total: 16s remaining: 44.1s
272: learn: 0.3141120 total: 16.1s remaining: 44s
273: learn: 0.3139170 total: 16.1s remaining: 43.9s
274: learn: 0.3136376 total: 16.2s remaining: 43.9s
275: learn: 0.3134766 total: 16.2s remaining: 43.8s
276: learn: 0.3133222 total: 16.3s remaining: 43.7s
277: learn: 0.3130430 total: 16.4s remaining: 43.6s
278: learn: 0.3127902 total: 16.4s remaining: 43.6s
279: learn: 0.3126530 total: 16.5s remaining: 43.5s
280: learn: 0.3124288 total: 16.5s remaining: 43.5s
281: learn: 0.3123350 total: 16.6s remaining: 43.4s
282: learn: 0.3120961 total: 16.6s remaining: 43.3s
283: learn: 0.3118921 total: 16.7s remaining: 43.3s
284: learn: 0.3118155 total: 16.7s remaining: 43.2s
285: learn: 0.3115726 total: 16.8s remaining: 43.1s
286: learn: 0.3114159 total: 16.9s remaining: 43.2s
287: learn: 0.3111223 total: 17s remaining: 43.1s
288: learn: 0.3108649 total: 17s remaining: 43s
289: learn: 0.3106370 total: 17.1s remaining: 43s
290: learn: 0.3104555 total: 17.1s remaining: 42.9s
291: learn: 0.3102824 total: 17.2s remaining: 42.8s
292: learn: 0.3100428 total: 17.2s remaining: 42.7s
293: learn: 0.3099023 total: 17.3s remaining: 42.6s
294: learn: 0.3098140 total: 17.3s remaining: 42.6s
295: learn: 0.3097360 total: 17.4s remaining: 42.5s
296: learn: 0.3095692 total: 17.4s remaining: 42.4s
297: learn: 0.3094997 total: 17.5s remaining: 42.3s
298: learn: 0.3093572 total: 17.5s remaining: 42.2s
299: learn: 0.3092190 total: 17.6s remaining: 42.1s
300: learn: 0.3091473 total: 17.6s remaining: 42.1s
301: learn: 0.3090086 total: 17.7s remaining: 42s
302: learn: 0.3087410 total: 17.7s remaining: 41.9s
303: learn: 0.3085711 total: 17.8s remaining: 41.8s
304: learn: 0.3084360 total: 17.8s remaining: 41.8s
305: learn: 0.3083208 total: 17.9s remaining: 41.7s
306: learn: 0.3080980 total: 17.9s remaining: 41.6s
307: learn: 0.3079752 total: 18s remaining: 41.5s
308: learn: 0.3075021 total: 18s remaining: 41.5s
309: learn: 0.3074112 total: 18.1s remaining: 41.4s
310: learn: 0.3072179 total: 18.1s remaining: 41.3s
311: learn: 0.3070817 total: 18.2s remaining: 41.3s
312: learn: 0.3069421 total: 18.2s remaining: 41.2s
313: learn: 0.3068440 total: 18.3s remaining: 41.1s
314: learn: 0.3067297 total: 18.4s remaining: 41.1s
315: learn: 0.3066471 total: 18.4s remaining: 41s
316: learn: 0.3065922 total: 18.5s remaining: 41s
317: learn: 0.3062758 total: 18.5s remaining: 40.9s
318: learn: 0.3060633 total: 18.6s remaining: 40.9s
319: learn: 0.3058005 total: 18.7s remaining: 40.8s
320: learn: 0.3055550 total: 18.7s remaining: 40.8s
321: learn: 0.3054304 total: 18.8s remaining: 40.7s
322: learn: 0.3053235 total: 18.8s remaining: 40.7s
323: learn: 0.3051363 total: 18.9s remaining: 40.6s
324: learn: 0.3049012 total: 19s remaining: 40.6s
325: learn: 0.3048674 total: 19s remaining: 40.5s
326: learn: 0.3047149 total: 19.1s remaining: 40.5s
327: learn: 0.3044916 total: 19.2s remaining: 40.4s
328: learn: 0.3043035 total: 19.2s remaining: 40.4s
329: learn: 0.3041932 total: 19.3s remaining: 40.3s
330: learn: 0.3039372 total: 19.3s remaining: 40.2s
331: learn: 0.3037969 total: 19.4s remaining: 40.2s
332: learn: 0.3036938 total: 19.5s remaining: 40.1s
333: learn: 0.3035681 total: 19.5s remaining: 40.1s
334: learn: 0.3033967 total: 19.6s remaining: 40s
335: learn: 0.3032605 total: 19.6s remaining: 40s
336: learn: 0.3031439 total: 19.7s remaining: 39.9s
337: learn: 0.3030063 total: 19.7s remaining: 39.8s
338: learn: 0.3028528 total: 19.8s remaining: 39.8s
339: learn: 0.3026978 total: 19.9s remaining: 39.7s
340: learn: 0.3024889 total: 19.9s remaining: 39.7s
341: learn: 0.3022965 total: 20s remaining: 39.6s
342: learn: 0.3020963 total: 20.1s remaining: 39.6s
343: learn: 0.3018895 total: 20.1s remaining: 39.5s
344: learn: 0.3018262 total: 20.2s remaining: 39.5s
345: learn: 0.3017120 total: 20.2s remaining: 39.4s
346: learn: 0.3016022 total: 20.3s remaining: 39.4s
347: learn: 0.3015467 total: 20.4s remaining: 39.3s
348: learn: 0.3014167 total: 20.4s remaining: 39.3s
349: learn: 0.3013460 total: 20.5s remaining: 39.2s
350: learn: 0.3011844 total: 20.6s remaining: 39.2s
351: learn: 0.3010353 total: 20.6s remaining: 39.1s
352: learn: 0.3009421 total: 20.7s remaining: 39.1s
353: learn: 0.3008509 total: 20.8s remaining: 39s
354: learn: 0.3006700 total: 20.8s remaining: 39s
355: learn: 0.3004220 total: 20.9s remaining: 39s
356: learn: 0.3003158 total: 21s remaining: 38.9s
357: learn: 0.3001591 total: 21s remaining: 38.9s
358: learn: 0.3000483 total: 21.1s remaining: 38.8s
359: learn: 0.2998369 total: 21.1s remaining: 38.8s
360: learn: 0.2997302 total: 21.2s remaining: 38.7s
361: learn: 0.2995649 total: 21.3s remaining: 38.7s
362: learn: 0.2994346 total: 21.3s remaining: 38.6s
363: learn: 0.2992380 total: 21.4s remaining: 38.6s
364: learn: 0.2990077 total: 21.5s remaining: 38.5s
365: learn: 0.2988929 total: 21.5s remaining: 38.5s
366: learn: 0.2987143 total: 21.6s remaining: 38.4s
367: learn: 0.2986176 total: 21.7s remaining: 38.4s
368: learn: 0.2984694 total: 21.7s remaining: 38.3s
369: learn: 0.2982943 total: 21.8s remaining: 38.2s
370: learn: 0.2980742 total: 21.8s remaining: 38.2s
371: learn: 0.2979344 total: 21.9s remaining: 38.1s
372: learn: 0.2976696 total: 21.9s remaining: 38s
373: learn: 0.2975657 total: 22s remaining: 37.9s
374: learn: 0.2974748 total: 22s remaining: 37.9s
375: learn: 0.2974305 total: 22.1s remaining: 37.8s
376: learn: 0.2972975 total: 22.1s remaining: 37.8s
377: learn: 0.2970900 total: 22.2s remaining: 37.7s
378: learn: 0.2969259 total: 22.3s remaining: 37.6s
379: learn: 0.2967467 total: 22.3s remaining: 37.6s
380: learn: 0.2966426 total: 22.4s remaining: 37.5s
381: learn: 0.2964828 total: 22.4s remaining: 37.4s
382: learn: 0.2963952 total: 22.5s remaining: 37.4s
383: learn: 0.2960183 total: 22.5s remaining: 37.3s
384: learn: 0.2956619 total: 22.6s remaining: 37.2s
385: learn: 0.2955178 total: 22.6s remaining: 37.2s
386: learn: 0.2953590 total: 22.7s remaining: 37.1s
387: learn: 0.2952293 total: 22.7s remaining: 37.1s
388: learn: 0.2950523 total: 22.8s remaining: 37s
389: learn: 0.2949705 total: 22.9s remaining: 36.9s
390: learn: 0.2948600 total: 22.9s remaining: 36.8s
391: learn: 0.2947835 total: 23s remaining: 36.8s
392: learn: 0.2945950 total: 23s remaining: 36.7s
393: learn: 0.2945315 total: 23.1s remaining: 36.7s
394: learn: 0.2944092 total: 23.1s remaining: 36.6s
395: learn: 0.2942953 total: 23.2s remaining: 36.5s
396: learn: 0.2940905 total: 23.2s remaining: 36.5s
397: learn: 0.2938680 total: 23.3s remaining: 36.4s
398: learn: 0.2937635 total: 23.4s remaining: 36.3s
399: learn: 0.2936922 total: 23.4s remaining: 36.3s
400: learn: 0.2935151 total: 23.5s remaining: 36.3s
401: learn: 0.2933855 total: 23.6s remaining: 36.2s
402: learn: 0.2932118 total: 23.6s remaining: 36.2s
403: learn: 0.2930308 total: 23.7s remaining: 36.2s
404: learn: 0.2929284 total: 23.8s remaining: 36.1s
405: learn: 0.2927616 total: 23.8s remaining: 36s
406: learn: 0.2925797 total: 23.9s remaining: 36s
407: learn: 0.2924601 total: 24s remaining: 35.9s
408: learn: 0.2923658 total: 24s remaining: 35.9s
409: learn: 0.2923052 total: 24.1s remaining: 35.8s
410: learn: 0.2920815 total: 24.1s remaining: 35.7s
411: learn: 0.2920157 total: 24.1s remaining: 35.6s
412: learn: 0.2918921 total: 24.2s remaining: 35.6s
413: learn: 0.2917421 total: 24.2s remaining: 35.5s
414: learn: 0.2916178 total: 24.3s remaining: 35.4s
415: learn: 0.2914174 total: 24.3s remaining: 35.3s
416: learn: 0.2912539 total: 24.4s remaining: 35.3s
417: learn: 0.2911301 total: 24.4s remaining: 35.2s
418: learn: 0.2910848 total: 24.5s remaining: 35.1s
419: learn: 0.2909676 total: 24.6s remaining: 35.1s
420: learn: 0.2907931 total: 24.6s remaining: 35s
421: learn: 0.2906038 total: 24.7s remaining: 35s
422: learn: 0.2904863 total: 24.7s remaining: 34.9s
423: learn: 0.2904627 total: 24.8s remaining: 34.9s
424: learn: 0.2903527 total: 24.9s remaining: 34.8s
425: learn: 0.2903228 total: 24.9s remaining: 34.7s
426: learn: 0.2902891 total: 25s remaining: 34.7s
427: learn: 0.2901026 total: 25.1s remaining: 34.7s
428: learn: 0.2899995 total: 25.2s remaining: 34.7s
429: learn: 0.2898813 total: 25.2s remaining: 34.6s
430: learn: 0.2898091 total: 25.3s remaining: 34.6s
431: learn: 0.2897395 total: 25.4s remaining: 34.5s
432: learn: 0.2896351 total: 25.4s remaining: 34.5s
433: learn: 0.2894068 total: 25.5s remaining: 34.4s
434: learn: 0.2892853 total: 25.5s remaining: 34.4s
435: learn: 0.2891553 total: 25.6s remaining: 34.3s
436: learn: 0.2890674 total: 25.7s remaining: 34.2s
437: learn: 0.2888972 total: 25.7s remaining: 34.2s
438: learn: 0.2887692 total: 25.8s remaining: 34.1s
439: learn: 0.2885679 total: 25.8s remaining: 34.1s
440: learn: 0.2884562 total: 25.9s remaining: 34s
441: learn: 0.2883899 total: 26s remaining: 33.9s
442: learn: 0.2883017 total: 26s remaining: 33.9s
443: learn: 0.2881783 total: 26.1s remaining: 33.8s
444: learn: 0.2880028 total: 26.1s remaining: 33.8s
445: learn: 0.2879390 total: 26.2s remaining: 33.7s
446: learn: 0.2878284 total: 26.3s remaining: 33.7s
447: learn: 0.2877006 total: 26.4s remaining: 33.6s
448: learn: 0.2875897 total: 26.4s remaining: 33.6s
449: learn: 0.2875434 total: 26.5s remaining: 33.5s
450: learn: 0.2873793 total: 26.5s remaining: 33.5s
451: learn: 0.2872886 total: 26.6s remaining: 33.4s
452: learn: 0.2871828 total: 26.7s remaining: 33.4s
453: learn: 0.2869686 total: 26.7s remaining: 33.3s
454: learn: 0.2868621 total: 26.8s remaining: 33.3s
455: learn: 0.2867378 total: 26.8s remaining: 33.2s
456: learn: 0.2865763 total: 26.9s remaining: 33.1s
457: learn: 0.2864662 total: 27s remaining: 33.1s
458: learn: 0.2862316 total: 27s remaining: 33.1s
459: learn: 0.2860501 total: 27.1s remaining: 33s
460: learn: 0.2858940 total: 27.2s remaining: 32.9s
461: learn: 0.2858091 total: 27.2s remaining: 32.9s
462: learn: 0.2857636 total: 27.3s remaining: 32.8s
463: learn: 0.2856579 total: 27.3s remaining: 32.8s
464: learn: 0.2856020 total: 27.4s remaining: 32.7s
465: learn: 0.2855151 total: 27.5s remaining: 32.7s
466: learn: 0.2854327 total: 27.5s remaining: 32.6s
467: learn: 0.2853733 total: 27.6s remaining: 32.6s
468: learn: 0.2852384 total: 27.7s remaining: 32.5s
469: learn: 0.2851375 total: 27.7s remaining: 32.4s
470: learn: 0.2850054 total: 27.8s remaining: 32.4s
471: learn: 0.2848557 total: 27.8s remaining: 32.3s
472: learn: 0.2847223 total: 27.9s remaining: 32.3s
473: learn: 0.2846506 total: 27.9s remaining: 32.2s
474: learn: 0.2844565 total: 28s remaining: 32.1s
475: learn: 0.2842743 total: 28.1s remaining: 32.1s
476: learn: 0.2841455 total: 28.1s remaining: 32s
477: learn: 0.2839059 total: 28.2s remaining: 32s
478: learn: 0.2838546 total: 28.2s remaining: 31.9s
479: learn: 0.2837393 total: 28.3s remaining: 31.8s
480: learn: 0.2836698 total: 28.4s remaining: 31.8s
481: learn: 0.2835916 total: 28.4s remaining: 31.7s
482: learn: 0.2835743 total: 28.5s remaining: 31.6s
483: learn: 0.2835172 total: 28.5s remaining: 31.6s
484: learn: 0.2834468 total: 28.6s remaining: 31.5s
485: learn: 0.2833309 total: 28.6s remaining: 31.4s
486: learn: 0.2832432 total: 28.7s remaining: 31.4s
487: learn: 0.2831696 total: 28.7s remaining: 31.3s
488: learn: 0.2831500 total: 28.8s remaining: 31.2s
489: learn: 0.2830511 total: 28.8s remaining: 31.2s
490: learn: 0.2829369 total: 28.9s remaining: 31.1s
491: learn: 0.2828718 total: 28.9s remaining: 31s
492: learn: 0.2827869 total: 29s remaining: 31s
493: learn: 0.2826849 total: 29s remaining: 30.9s
494: learn: 0.2825850 total: 29.1s remaining: 30.8s
495: learn: 0.2823185 total: 29.1s remaining: 30.7s
496: learn: 0.2822332 total: 29.2s remaining: 30.7s
497: learn: 0.2821659 total: 29.2s remaining: 30.6s
498: learn: 0.2820806 total: 29.3s remaining: 30.6s
499: learn: 0.2820227 total: 29.3s remaining: 30.5s
500: learn: 0.2819141 total: 29.4s remaining: 30.5s
501: learn: 0.2818356 total: 29.5s remaining: 30.4s
502: learn: 0.2815730 total: 29.5s remaining: 30.3s
503: learn: 0.2815112 total: 29.6s remaining: 30.3s
504: learn: 0.2813090 total: 29.6s remaining: 30.2s
505: learn: 0.2811150 total: 29.7s remaining: 30.1s
506: learn: 0.2810516 total: 29.7s remaining: 30.1s
507: learn: 0.2808077 total: 29.8s remaining: 30s
508: learn: 0.2807643 total: 29.9s remaining: 30s
509: learn: 0.2806992 total: 29.9s remaining: 29.9s
510: learn: 0.2806000 total: 30s remaining: 29.8s
511: learn: 0.2804235 total: 30s remaining: 29.8s
512: learn: 0.2803421 total: 30.1s remaining: 29.7s
513: learn: 0.2802449 total: 30.1s remaining: 29.7s
514: learn: 0.2802300 total: 30.2s remaining: 29.6s
515: learn: 0.2799361 total: 30.3s remaining: 29.5s
516: learn: 0.2797783 total: 30.3s remaining: 29.5s
517: learn: 0.2797122 total: 30.4s remaining: 29.5s
518: learn: 0.2795900 total: 30.4s remaining: 29.4s
519: learn: 0.2795009 total: 30.5s remaining: 29.3s
520: learn: 0.2793893 total: 30.6s remaining: 29.3s
521: learn: 0.2793211 total: 30.6s remaining: 29.2s
522: learn: 0.2791499 total: 30.7s remaining: 29.1s
523: learn: 0.2790619 total: 30.7s remaining: 29.1s
524: learn: 0.2790453 total: 30.8s remaining: 29s
525: learn: 0.2789829 total: 30.8s remaining: 28.9s
526: learn: 0.2787060 total: 30.9s remaining: 28.9s
527: learn: 0.2786493 total: 30.9s remaining: 28.8s
528: learn: 0.2785265 total: 31s remaining: 28.8s
529: learn: 0.2784407 total: 31.1s remaining: 28.7s
530: learn: 0.2781306 total: 31.1s remaining: 28.7s
531: learn: 0.2779846 total: 31.2s remaining: 28.6s
532: learn: 0.2779266 total: 31.2s remaining: 28.5s
533: learn: 0.2778407 total: 31.3s remaining: 28.5s
534: learn: 0.2777767 total: 31.3s remaining: 28.4s
535: learn: 0.2776582 total: 31.4s remaining: 28.3s
536: learn: 0.2775760 total: 31.4s remaining: 28.3s
537: learn: 0.2774862 total: 31.5s remaining: 28.2s
538: learn: 0.2773881 total: 31.5s remaining: 28.1s
539: learn: 0.2771933 total: 31.6s remaining: 28.1s
540: learn: 0.2771344 total: 31.6s remaining: 28s
541: learn: 0.2770617 total: 31.7s remaining: 28s
542: learn: 0.2769112 total: 31.8s remaining: 27.9s
543: learn: 0.2767745 total: 31.8s remaining: 27.8s
544: learn: 0.2766887 total: 31.9s remaining: 27.8s
545: learn: 0.2766655 total: 31.9s remaining: 27.7s
546: learn: 0.2765456 total: 32s remaining: 27.7s
547: learn: 0.2764987 total: 32s remaining: 27.6s
548: learn: 0.2763347 total: 32.1s remaining: 27.5s
549: learn: 0.2761366 total: 32.1s remaining: 27.5s
550: learn: 0.2760529 total: 32.2s remaining: 27.4s
551: learn: 0.2759967 total: 32.3s remaining: 27.4s
552: learn: 0.2758365 total: 32.3s remaining: 27.3s
553: learn: 0.2757807 total: 32.4s remaining: 27.2s
554: learn: 0.2757239 total: 32.4s remaining: 27.2s
555: learn: 0.2756680 total: 32.5s remaining: 27.1s
556: learn: 0.2754426 total: 32.5s remaining: 27.1s
557: learn: 0.2753433 total: 32.6s remaining: 27s
558: learn: 0.2752289 total: 32.6s remaining: 26.9s
559: learn: 0.2750652 total: 32.7s remaining: 26.9s
560: learn: 0.2749651 total: 32.8s remaining: 26.8s
561: learn: 0.2748879 total: 32.8s remaining: 26.7s
562: learn: 0.2747587 total: 32.9s remaining: 26.7s
563: learn: 0.2746254 total: 32.9s remaining: 26.6s
564: learn: 0.2745264 total: 33s remaining: 26.6s
565: learn: 0.2744176 total: 33s remaining: 26.5s
566: learn: 0.2742878 total: 33.1s remaining: 26.4s
567: learn: 0.2741974 total: 33.1s remaining: 26.4s
568: learn: 0.2741063 total: 33.2s remaining: 26.3s
569: learn: 0.2740522 total: 33.2s remaining: 26.2s
570: learn: 0.2739113 total: 33.3s remaining: 26.2s
571: learn: 0.2738544 total: 33.4s remaining: 26.1s
572: learn: 0.2738119 total: 33.4s remaining: 26.1s
573: learn: 0.2737698 total: 33.5s remaining: 26s
574: learn: 0.2737424 total: 33.5s remaining: 25.9s
575: learn: 0.2736590 total: 33.6s remaining: 25.9s
576: learn: 0.2735589 total: 33.6s remaining: 25.8s
577: learn: 0.2734517 total: 33.7s remaining: 25.7s
578: learn: 0.2734516 total: 33.7s remaining: 25.6s
579: learn: 0.2733980 total: 33.7s remaining: 25.6s
580: learn: 0.2733037 total: 33.8s remaining: 25.5s
581: learn: 0.2732480 total: 33.8s remaining: 25.5s
582: learn: 0.2730859 total: 33.9s remaining: 25.4s
583: learn: 0.2730155 total: 34s remaining: 25.4s
584: learn: 0.2728653 total: 34s remaining: 25.3s
585: learn: 0.2728137 total: 34.1s remaining: 25.2s
586: learn: 0.2726969 total: 34.1s remaining: 25.2s
587: learn: 0.2726381 total: 34.2s remaining: 25.1s
588: learn: 0.2725373 total: 34.3s remaining: 25.1s
589: learn: 0.2724669 total: 34.3s remaining: 25s
590: learn: 0.2723931 total: 34.4s remaining: 25s
591: learn: 0.2721381 total: 34.4s remaining: 24.9s
592: learn: 0.2720861 total: 34.5s remaining: 24.9s
593: learn: 0.2720123 total: 34.6s remaining: 24.8s
594: learn: 0.2719467 total: 34.7s remaining: 24.8s
595: learn: 0.2718413 total: 34.7s remaining: 24.7s
596: learn: 0.2717786 total: 34.8s remaining: 24.6s
597: learn: 0.2716258 total: 34.9s remaining: 24.6s
598: learn: 0.2715435 total: 34.9s remaining: 24.5s
599: learn: 0.2714521 total: 35s remaining: 24.5s
600: learn: 0.2712928 total: 35.1s remaining: 24.4s
601: learn: 0.2712045 total: 35.1s remaining: 24.4s
602: learn: 0.2711668 total: 35.2s remaining: 24.3s
603: learn: 0.2711230 total: 35.2s remaining: 24.3s
604: learn: 0.2710543 total: 35.3s remaining: 24.2s
605: learn: 0.2709419 total: 35.4s remaining: 24.2s
606: learn: 0.2708444 total: 35.4s remaining: 24.1s
607: learn: 0.2707043 total: 35.5s remaining: 24.1s
608: learn: 0.2706165 total: 35.6s remaining: 24s
609: learn: 0.2704741 total: 35.6s remaining: 23.9s
610: learn: 0.2703886 total: 35.7s remaining: 23.9s
611: learn: 0.2703313 total: 35.8s remaining: 23.8s
612: learn: 0.2702451 total: 35.8s remaining: 23.8s
613: learn: 0.2701492 total: 35.9s remaining: 23.8s
614: learn: 0.2700665 total: 36s remaining: 23.7s
615: learn: 0.2700168 total: 36s remaining: 23.6s
616: learn: 0.2699423 total: 36.1s remaining: 23.6s
617: learn: 0.2698117 total: 36.2s remaining: 23.5s
618: learn: 0.2696609 total: 36.2s remaining: 23.5s
619: learn: 0.2695728 total: 36.3s remaining: 23.4s
620: learn: 0.2694905 total: 36.4s remaining: 23.4s
621: learn: 0.2693321 total: 36.4s remaining: 23.3s
622: learn: 0.2692840 total: 36.5s remaining: 23.3s
623: learn: 0.2692462 total: 36.6s remaining: 23.2s
624: learn: 0.2691908 total: 36.6s remaining: 23.1s
625: learn: 0.2691858 total: 36.7s remaining: 23.1s
626: learn: 0.2691574 total: 36.8s remaining: 23s
627: learn: 0.2690805 total: 36.8s remaining: 23s
628: learn: 0.2690131 total: 36.9s remaining: 22.9s
629: learn: 0.2688749 total: 37s remaining: 22.9s
630: learn: 0.2688748 total: 37s remaining: 22.8s
631: learn: 0.2688584 total: 37.1s remaining: 22.8s
632: learn: 0.2688138 total: 37.2s remaining: 22.7s
633: learn: 0.2687763 total: 37.2s remaining: 22.7s
634: learn: 0.2687635 total: 37.3s remaining: 22.6s
635: learn: 0.2686483 total: 37.4s remaining: 22.6s
636: learn: 0.2683496 total: 37.4s remaining: 22.5s
637: learn: 0.2682925 total: 37.5s remaining: 22.4s
638: learn: 0.2682924 total: 37.5s remaining: 22.4s
639: learn: 0.2682755 total: 37.6s remaining: 22.3s
640: learn: 0.2681955 total: 37.6s remaining: 22.2s
641: learn: 0.2681530 total: 37.7s remaining: 22.2s
642: learn: 0.2681404 total: 37.7s remaining: 22.1s
643: learn: 0.2679839 total: 37.8s remaining: 22.1s
644: learn: 0.2678824 total: 37.8s remaining: 22s
645: learn: 0.2677943 total: 37.9s remaining: 21.9s
646: learn: 0.2677436 total: 37.9s remaining: 21.9s
647: learn: 0.2674949 total: 38s remaining: 21.8s
648: learn: 0.2673912 total: 38s remaining: 21.7s
649: learn: 0.2673163 total: 38.1s remaining: 21.7s
650: learn: 0.2672625 total: 38.2s remaining: 21.6s
651: learn: 0.2671826 total: 38.2s remaining: 21.6s
652: learn: 0.2671689 total: 38.3s remaining: 21.5s
653: learn: 0.2671071 total: 38.3s remaining: 21.4s
654: learn: 0.2669445 total: 38.4s remaining: 21.4s
655: learn: 0.2668765 total: 38.4s remaining: 21.3s
656: learn: 0.2668353 total: 38.5s remaining: 21.3s
657: learn: 0.2667761 total: 38.5s remaining: 21.2s
658: learn: 0.2666779 total: 38.6s remaining: 21.1s
659: learn: 0.2666069 total: 38.6s remaining: 21.1s
660: learn: 0.2664870 total: 38.7s remaining: 21s
661: learn: 0.2664456 total: 38.7s remaining: 20.9s
662: learn: 0.2663467 total: 38.8s remaining: 20.9s
663: learn: 0.2663359 total: 38.8s remaining: 20.8s
664: learn: 0.2662501 total: 38.9s remaining: 20.7s
665: learn: 0.2661615 total: 38.9s remaining: 20.7s
666: learn: 0.2660734 total: 39s remaining: 20.6s
667: learn: 0.2660292 total: 39s remaining: 20.6s
668: learn: 0.2658926 total: 39.1s remaining: 20.5s
669: learn: 0.2657838 total: 39.2s remaining: 20.5s
670: learn: 0.2657167 total: 39.2s remaining: 20.4s
671: learn: 0.2656024 total: 39.3s remaining: 20.3s
672: learn: 0.2655287 total: 39.3s remaining: 20.3s
673: learn: 0.2654259 total: 39.4s remaining: 20.2s
674: learn: 0.2653380 total: 39.4s remaining: 20.1s
675: learn: 0.2652000 total: 39.5s remaining: 20.1s
676: learn: 0.2650979 total: 39.5s remaining: 20s
677: learn: 0.2650503 total: 39.6s remaining: 20s
678: learn: 0.2650220 total: 39.6s remaining: 19.9s
679: learn: 0.2650108 total: 39.8s remaining: 19.9s
680: learn: 0.2649882 total: 39.9s remaining: 19.8s
681: learn: 0.2648791 total: 39.9s remaining: 19.8s
682: learn: 0.2647971 total: 40s remaining: 19.7s
683: learn: 0.2647343 total: 40s remaining: 19.7s
684: learn: 0.2646020 total: 40.1s remaining: 19.6s
685: learn: 0.2645409 total: 40.1s remaining: 19.5s
686: learn: 0.2644741 total: 40.2s remaining: 19.5s
687: learn: 0.2643603 total: 40.2s remaining: 19.4s
688: learn: 0.2642626 total: 40.3s remaining: 19.4s
689: learn: 0.2640762 total: 40.4s remaining: 19.3s
690: learn: 0.2640139 total: 40.4s remaining: 19.2s
691: learn: 0.2639091 total: 40.5s remaining: 19.2s
692: learn: 0.2638273 total: 40.5s remaining: 19.1s
693: learn: 0.2637916 total: 40.6s remaining: 19.1s
694: learn: 0.2637452 total: 40.6s remaining: 19s
695: learn: 0.2635668 total: 40.7s remaining: 18.9s
696: learn: 0.2634930 total: 40.7s remaining: 18.9s
697: learn: 0.2634703 total: 40.8s remaining: 18.8s
698: learn: 0.2634403 total: 40.8s remaining: 18.7s
699: learn: 0.2634008 total: 40.9s remaining: 18.7s
700: learn: 0.2633651 total: 40.9s remaining: 18.6s
701: learn: 0.2633012 total: 41s remaining: 18.6s
702: learn: 0.2632144 total: 41s remaining: 18.5s
703: learn: 0.2632037 total: 41.1s remaining: 18.4s
704: learn: 0.2630602 total: 41.1s remaining: 18.4s
705: learn: 0.2630088 total: 41.2s remaining: 18.3s
706: learn: 0.2629343 total: 41.2s remaining: 18.3s
707: learn: 0.2629342 total: 41.3s remaining: 18.2s
708: learn: 0.2629112 total: 41.3s remaining: 18.1s
709: learn: 0.2627056 total: 41.4s remaining: 18.1s
710: learn: 0.2626611 total: 41.4s remaining: 18s
711: learn: 0.2626206 total: 41.5s remaining: 17.9s
712: learn: 0.2625750 total: 41.5s remaining: 17.9s
713: learn: 0.2624152 total: 41.6s remaining: 17.8s
714: learn: 0.2622447 total: 41.6s remaining: 17.8s
715: learn: 0.2621700 total: 41.7s remaining: 17.7s
716: learn: 0.2621268 total: 41.8s remaining: 17.6s
717: learn: 0.2620129 total: 41.8s remaining: 17.6s
718: learn: 0.2619031 total: 41.9s remaining: 17.5s
719: learn: 0.2618872 total: 41.9s remaining: 17.5s
720: learn: 0.2618393 total: 42s remaining: 17.4s
721: learn: 0.2617888 total: 42s remaining: 17.4s
722: learn: 0.2617672 total: 42.1s remaining: 17.3s
723: learn: 0.2617535 total: 42.2s remaining: 17.2s
724: learn: 0.2616580 total: 42.2s remaining: 17.2s
725: learn: 0.2615449 total: 42.3s remaining: 17.1s
726: learn: 0.2614615 total: 42.3s remaining: 17.1s
727: learn: 0.2614076 total: 42.4s remaining: 17s
728: learn: 0.2613401 total: 42.4s remaining: 16.9s
729: learn: 0.2612865 total: 42.5s remaining: 16.9s
730: learn: 0.2612306 total: 42.6s remaining: 16.8s
731: learn: 0.2611581 total: 42.7s remaining: 16.8s
732: learn: 0.2610897 total: 42.7s remaining: 16.7s
733: learn: 0.2610230 total: 42.8s remaining: 16.7s
734: learn: 0.2610158 total: 42.8s remaining: 16.6s
735: learn: 0.2609876 total: 42.9s remaining: 16.5s
736: learn: 0.2609665 total: 42.9s remaining: 16.5s
737: learn: 0.2609597 total: 42.9s remaining: 16.4s
738: learn: 0.2608845 total: 43s remaining: 16.4s
739: learn: 0.2608089 total: 43.1s remaining: 16.3s
740: learn: 0.2607610 total: 43.1s remaining: 16.2s
741: learn: 0.2606750 total: 43.2s remaining: 16.2s
742: learn: 0.2606459 total: 43.2s remaining: 16.1s
743: learn: 0.2605477 total: 43.3s remaining: 16s
744: learn: 0.2604986 total: 43.3s remaining: 16s
745: learn: 0.2604430 total: 43.4s remaining: 15.9s
746: learn: 0.2603149 total: 43.4s remaining: 15.9s
747: learn: 0.2601973 total: 43.5s remaining: 15.8s
748: learn: 0.2601445 total: 43.5s remaining: 15.7s
749: learn: 0.2600395 total: 43.6s remaining: 15.7s
750: learn: 0.2599489 total: 43.6s remaining: 15.6s
751: learn: 0.2598767 total: 43.7s remaining: 15.6s
752: learn: 0.2597904 total: 43.7s remaining: 15.5s
753: learn: 0.2597450 total: 43.8s remaining: 15.5s
754: learn: 0.2597070 total: 43.9s remaining: 15.4s
755: learn: 0.2596589 total: 43.9s remaining: 15.3s
756: learn: 0.2595803 total: 44s remaining: 15.3s
757: learn: 0.2594804 total: 44s remaining: 15.2s
758: learn: 0.2593713 total: 44.1s remaining: 15.2s
759: learn: 0.2593712 total: 44.1s remaining: 15.1s
760: learn: 0.2593273 total: 44.1s remaining: 15s
761: learn: 0.2592264 total: 44.2s remaining: 15s
762: learn: 0.2591824 total: 44.3s remaining: 14.9s
763: learn: 0.2591287 total: 44.3s remaining: 14.8s
764: learn: 0.2590385 total: 44.4s remaining: 14.8s
765: learn: 0.2590273 total: 44.4s remaining: 14.7s
766: learn: 0.2589855 total: 44.5s remaining: 14.7s
767: learn: 0.2588782 total: 44.5s remaining: 14.6s
768: learn: 0.2588575 total: 44.6s remaining: 14.6s
769: learn: 0.2588358 total: 44.6s remaining: 14.5s
770: learn: 0.2588162 total: 44.7s remaining: 14.4s
771: learn: 0.2587872 total: 44.7s remaining: 14.4s
772: learn: 0.2587087 total: 44.8s remaining: 14.3s
773: learn: 0.2586084 total: 44.8s remaining: 14.3s
774: learn: 0.2584877 total: 44.9s remaining: 14.2s
775: learn: 0.2583974 total: 45s remaining: 14.1s
776: learn: 0.2583270 total: 45s remaining: 14.1s
777: learn: 0.2582897 total: 45.1s remaining: 14s
778: learn: 0.2582289 total: 45.1s remaining: 14s
779: learn: 0.2581925 total: 45.2s remaining: 13.9s
780: learn: 0.2581477 total: 45.2s remaining: 13.8s
781: learn: 0.2580964 total: 45.3s remaining: 13.8s
782: learn: 0.2580560 total: 45.3s remaining: 13.7s
783: learn: 0.2578723 total: 45.4s remaining: 13.7s
784: learn: 0.2578327 total: 45.5s remaining: 13.6s
785: learn: 0.2578063 total: 45.5s remaining: 13.6s
786: learn: 0.2577096 total: 45.6s remaining: 13.5s
787: learn: 0.2575740 total: 45.6s remaining: 13.4s
788: learn: 0.2574928 total: 45.7s remaining: 13.4s
789: learn: 0.2573671 total: 45.8s remaining: 13.3s
790: learn: 0.2572733 total: 45.8s remaining: 13.3s
791: learn: 0.2571322 total: 45.9s remaining: 13.2s
792: learn: 0.2570512 total: 46s remaining: 13.2s
793: learn: 0.2570120 total: 46s remaining: 13.1s
794: learn: 0.2569302 total: 46.1s remaining: 13s
795: learn: 0.2569114 total: 46.1s remaining: 13s
796: learn: 0.2569091 total: 46.2s remaining: 12.9s
797: learn: 0.2568772 total: 46.3s remaining: 12.9s
798: learn: 0.2568606 total: 46.3s remaining: 12.8s
799: learn: 0.2568007 total: 46.4s remaining: 12.8s
800: learn: 0.2566366 total: 46.5s remaining: 12.7s
801: learn: 0.2565830 total: 46.5s remaining: 12.6s
802: learn: 0.2564715 total: 46.6s remaining: 12.6s
803: learn: 0.2564174 total: 46.6s remaining: 12.5s
804: learn: 0.2563117 total: 46.7s remaining: 12.5s
805: learn: 0.2562428 total: 46.8s remaining: 12.4s
806: learn: 0.2561924 total: 46.8s remaining: 12.4s
807: learn: 0.2560410 total: 46.9s remaining: 12.3s
808: learn: 0.2560394 total: 46.9s remaining: 12.2s
809: learn: 0.2559930 total: 47s remaining: 12.2s
810: learn: 0.2559282 total: 47.1s remaining: 12.1s
811: learn: 0.2559195 total: 47.1s remaining: 12.1s
812: learn: 0.2558753 total: 47.2s remaining: 12s
813: learn: 0.2558381 total: 47.3s remaining: 12s
814: learn: 0.2558036 total: 47.3s remaining: 11.9s
815: learn: 0.2557516 total: 47.4s remaining: 11.8s
816: learn: 0.2555012 total: 47.4s remaining: 11.8s
817: learn: 0.2553996 total: 47.5s remaining: 11.7s
818: learn: 0.2553509 total: 47.6s remaining: 11.7s
819: learn: 0.2552906 total: 47.6s remaining: 11.6s
820: learn: 0.2552658 total: 47.7s remaining: 11.6s
821: learn: 0.2552449 total: 47.7s remaining: 11.5s
822: learn: 0.2552003 total: 47.8s remaining: 11.4s
823: learn: 0.2551783 total: 47.9s remaining: 11.4s
824: learn: 0.2551442 total: 47.9s remaining: 11.3s
825: learn: 0.2550461 total: 48s remaining: 11.3s
826: learn: 0.2549387 total: 48s remaining: 11.2s
827: learn: 0.2548371 total: 48.1s remaining: 11.2s
828: learn: 0.2548290 total: 48.2s remaining: 11.1s
829: learn: 0.2547524 total: 48.2s remaining: 11s
830: learn: 0.2547011 total: 48.3s remaining: 11s
831: learn: 0.2546699 total: 48.4s remaining: 10.9s
832: learn: 0.2546515 total: 48.4s remaining: 10.9s
833: learn: 0.2544575 total: 48.5s remaining: 10.8s
834: learn: 0.2543946 total: 48.6s remaining: 10.8s
835: learn: 0.2541653 total: 48.6s remaining: 10.7s
836: learn: 0.2541316 total: 48.7s remaining: 10.6s
837: learn: 0.2541011 total: 48.7s remaining: 10.6s
838: learn: 0.2540312 total: 48.8s remaining: 10.5s
839: learn: 0.2539293 total: 48.8s remaining: 10.5s
840: learn: 0.2539166 total: 48.9s remaining: 10.4s
841: learn: 0.2539027 total: 48.9s remaining: 10.3s
842: learn: 0.2538382 total: 49s remaining: 10.3s
843: learn: 0.2537541 total: 49s remaining: 10.2s
844: learn: 0.2536711 total: 49.1s remaining: 10.2s
845: learn: 0.2535633 total: 49.1s remaining: 10.1s
846: learn: 0.2534843 total: 49.2s remaining: 10s
847: learn: 0.2534584 total: 49.2s remaining: 9.99s
848: learn: 0.2534030 total: 49.3s remaining: 9.93s
849: learn: 0.2532678 total: 49.3s remaining: 9.87s
850: learn: 0.2532218 total: 49.4s remaining: 9.81s
851: learn: 0.2531725 total: 49.5s remaining: 9.76s
852: learn: 0.2531580 total: 49.5s remaining: 9.7s
853: learn: 0.2531315 total: 49.6s remaining: 9.64s
854: learn: 0.2530175 total: 49.6s remaining: 9.58s
855: learn: 0.2529262 total: 49.7s remaining: 9.52s
856: learn: 0.2528015 total: 49.7s remaining: 9.46s
857: learn: 0.2527508 total: 49.8s remaining: 9.4s
858: learn: 0.2526960 total: 49.8s remaining: 9.34s
859: learn: 0.2526563 total: 49.9s remaining: 9.28s
860: learn: 0.2526562 total: 49.9s remaining: 9.21s
861: learn: 0.2526311 total: 50s remaining: 9.16s
862: learn: 0.2526186 total: 50s remaining: 9.1s
863: learn: 0.2525383 total: 50.1s remaining: 9.04s
864: learn: 0.2525283 total: 50.1s remaining: 8.98s
865: learn: 0.2524698 total: 50.2s remaining: 8.92s
866: learn: 0.2524272 total: 50.2s remaining: 8.86s
867: learn: 0.2524166 total: 50.3s remaining: 8.8s
868: learn: 0.2523821 total: 50.3s remaining: 8.74s
869: learn: 0.2522800 total: 50.4s remaining: 8.68s
870: learn: 0.2522335 total: 50.4s remaining: 8.63s
871: learn: 0.2521300 total: 50.5s remaining: 8.57s
872: learn: 0.2520945 total: 50.5s remaining: 8.51s
873: learn: 0.2520207 total: 50.6s remaining: 8.45s
874: learn: 0.2519531 total: 50.6s remaining: 8.39s
875: learn: 0.2519243 total: 50.7s remaining: 8.33s
876: learn: 0.2518005 total: 50.7s remaining: 8.27s
877: learn: 0.2517925 total: 50.8s remaining: 8.21s
878: learn: 0.2517633 total: 50.8s remaining: 8.15s
879: learn: 0.2517413 total: 50.9s remaining: 8.1s
880: learn: 0.2516852 total: 50.9s remaining: 8.04s
881: learn: 0.2516672 total: 51s remaining: 7.98s
882: learn: 0.2516457 total: 51s remaining: 7.92s
883: learn: 0.2516117 total: 51.1s remaining: 7.86s
884: learn: 0.2515947 total: 51.2s remaining: 7.8s
885: learn: 0.2515654 total: 51.2s remaining: 7.74s
886: learn: 0.2514138 total: 51.3s remaining: 7.68s
887: learn: 0.2513197 total: 51.3s remaining: 7.63s
888: learn: 0.2512626 total: 51.4s remaining: 7.57s
889: learn: 0.2511992 total: 51.4s remaining: 7.51s
890: learn: 0.2510398 total: 51.5s remaining: 7.45s
891: learn: 0.2510069 total: 51.5s remaining: 7.39s
892: learn: 0.2509333 total: 51.6s remaining: 7.33s
893: learn: 0.2508858 total: 51.6s remaining: 7.28s
894: learn: 0.2508107 total: 51.7s remaining: 7.22s
895: learn: 0.2507662 total: 51.7s remaining: 7.16s
896: learn: 0.2507001 total: 51.8s remaining: 7.1s
897: learn: 0.2506254 total: 51.8s remaining: 7.04s
898: learn: 0.2505740 total: 51.9s remaining: 6.98s
899: learn: 0.2505739 total: 51.9s remaining: 6.92s
900: learn: 0.2505605 total: 52s remaining: 6.86s
901: learn: 0.2505497 total: 52s remaining: 6.8s
902: learn: 0.2504432 total: 52.1s remaining: 6.75s
903: learn: 0.2503726 total: 52.1s remaining: 6.69s
904: learn: 0.2503230 total: 52.2s remaining: 6.63s
905: learn: 0.2502621 total: 52.2s remaining: 6.57s
906: learn: 0.2500956 total: 52.3s remaining: 6.52s
907: learn: 0.2500395 total: 52.4s remaining: 6.46s
908: learn: 0.2499562 total: 52.4s remaining: 6.4s
909: learn: 0.2498668 total: 52.5s remaining: 6.35s
910: learn: 0.2498080 total: 52.6s remaining: 6.29s
911: learn: 0.2497442 total: 52.6s remaining: 6.23s
912: learn: 0.2497006 total: 52.7s remaining: 6.17s
913: learn: 0.2496873 total: 52.8s remaining: 6.12s
914: learn: 0.2495958 total: 52.8s remaining: 6.06s
915: learn: 0.2495358 total: 52.9s remaining: 6s
916: learn: 0.2494716 total: 53s remaining: 5.95s
917: learn: 0.2493739 total: 53s remaining: 5.89s
918: learn: 0.2492786 total: 53.1s remaining: 5.83s
919: learn: 0.2491095 total: 53.1s remaining: 5.78s
920: learn: 0.2490502 total: 53.2s remaining: 5.72s
921: learn: 0.2489579 total: 53.3s remaining: 5.66s
922: learn: 0.2488567 total: 53.3s remaining: 5.61s
923: learn: 0.2487836 total: 53.4s remaining: 5.55s
924: learn: 0.2487495 total: 53.5s remaining: 5.49s
925: learn: 0.2487242 total: 53.5s remaining: 5.43s
926: learn: 0.2486954 total: 53.6s remaining: 5.38s
927: learn: 0.2486654 total: 53.7s remaining: 5.32s
928: learn: 0.2486562 total: 53.7s remaining: 5.26s
929: learn: 0.2485970 total: 53.8s remaining: 5.2s
930: learn: 0.2485602 total: 53.8s remaining: 5.15s
931: learn: 0.2485212 total: 53.9s remaining: 5.09s
932: learn: 0.2484966 total: 54s remaining: 5.03s
933: learn: 0.2484383 total: 54s remaining: 4.97s
934: learn: 0.2484183 total: 54.1s remaining: 4.92s
935: learn: 0.2483854 total: 54.1s remaining: 4.86s
936: learn: 0.2483216 total: 54.2s remaining: 4.8s
937: learn: 0.2482922 total: 54.3s remaining: 4.74s
938: learn: 0.2482537 total: 54.3s remaining: 4.69s
939: learn: 0.2481728 total: 54.4s remaining: 4.63s
940: learn: 0.2481628 total: 54.5s remaining: 4.57s
941: learn: 0.2481324 total: 54.5s remaining: 4.51s
942: learn: 0.2480314 total: 54.6s remaining: 4.46s
943: learn: 0.2480120 total: 54.6s remaining: 4.4s
944: learn: 0.2479852 total: 54.7s remaining: 4.34s
945: learn: 0.2479685 total: 54.8s remaining: 4.28s
946: learn: 0.2479497 total: 54.8s remaining: 4.23s
947: learn: 0.2478871 total: 54.9s remaining: 4.17s
948: learn: 0.2478326 total: 54.9s remaining: 4.11s
949: learn: 0.2477939 total: 55s remaining: 4.05s
950: learn: 0.2477495 total: 55.1s remaining: 4s
951: learn: 0.2477342 total: 55.1s remaining: 3.94s
952: learn: 0.2477223 total: 55.2s remaining: 3.88s
953: learn: 0.2476845 total: 55.2s remaining: 3.82s
954: learn: 0.2475418 total: 55.3s remaining: 3.76s
955: learn: 0.2474909 total: 55.4s remaining: 3.71s
956: learn: 0.2474581 total: 55.4s remaining: 3.65s
957: learn: 0.2474403 total: 55.5s remaining: 3.59s
958: learn: 0.2473509 total: 55.5s remaining: 3.53s
959: learn: 0.2473258 total: 55.6s remaining: 3.47s
960: learn: 0.2471587 total: 55.7s remaining: 3.42s
961: learn: 0.2470890 total: 55.7s remaining: 3.36s
962: learn: 0.2470695 total: 55.8s remaining: 3.3s
963: learn: 0.2470660 total: 55.8s remaining: 3.24s
964: learn: 0.2470417 total: 55.9s remaining: 3.18s
965: learn: 0.2469405 total: 55.9s remaining: 3.13s
966: learn: 0.2468474 total: 56s remaining: 3.07s
967: learn: 0.2468333 total: 56s remaining: 3.01s
968: learn: 0.2468328 total: 56.1s remaining: 2.95s
969: learn: 0.2467655 total: 56.1s remaining: 2.89s
970: learn: 0.2467179 total: 56.2s remaining: 2.83s
971: learn: 0.2467049 total: 56.2s remaining: 2.77s
972: learn: 0.2467041 total: 56.3s remaining: 2.72s
973: learn: 0.2466789 total: 56.3s remaining: 2.66s
974: learn: 0.2465946 total: 56.4s remaining: 2.6s
975: learn: 0.2465941 total: 56.4s remaining: 2.54s
976: learn: 0.2465850 total: 56.5s remaining: 2.48s
977: learn: 0.2465197 total: 56.5s remaining: 2.43s
978: learn: 0.2464843 total: 56.6s remaining: 2.37s
979: learn: 0.2463673 total: 56.6s remaining: 2.31s
980: learn: 0.2463299 total: 56.7s remaining: 2.25s
981: learn: 0.2462523 total: 56.7s remaining: 2.19s
982: learn: 0.2461975 total: 56.8s remaining: 2.14s
983: learn: 0.2461554 total: 56.8s remaining: 2.08s
984: learn: 0.2461085 total: 56.9s remaining: 2.02s
985: learn: 0.2460311 total: 56.9s remaining: 1.96s
986: learn: 0.2460310 total: 56.9s remaining: 1.9s
987: learn: 0.2459969 total: 57s remaining: 1.84s
988: learn: 0.2459704 total: 57s remaining: 1.79s
989: learn: 0.2459604 total: 57.1s remaining: 1.73s
990: learn: 0.2459461 total: 57.1s remaining: 1.67s
991: learn: 0.2459104 total: 57.2s remaining: 1.61s
992: learn: 0.2459100 total: 57.2s remaining: 1.55s
993: learn: 0.2458916 total: 57.3s remaining: 1.5s
994: learn: 0.2458155 total: 57.3s remaining: 1.44s
995: learn: 0.2458137 total: 57.4s remaining: 1.38s
996: learn: 0.2457927 total: 57.4s remaining: 1.32s
997: learn: 0.2456271 total: 57.5s remaining: 1.27s
998: learn: 0.2456157 total: 57.5s remaining: 1.21s
999: learn: 0.2456032 total: 57.6s remaining: 1.15s
1000: learn: 0.2455608 total: 57.6s remaining: 1.09s
1001: learn: 0.2455333 total: 57.7s remaining: 1.04s
1002: learn: 0.2453509 total: 57.7s remaining: 979ms
1003: learn: 0.2453283 total: 57.8s remaining: 921ms
1004: learn: 0.2453281 total: 57.8s remaining: 863ms
1005: learn: 0.2453197 total: 57.9s remaining: 805ms
1006: learn: 0.2452616 total: 57.9s remaining: 748ms
1007: learn: 0.2451964 total: 58s remaining: 690ms
1008: learn: 0.2451731 total: 58s remaining: 633ms
1009: learn: 0.2450927 total: 58.1s remaining: 575ms
1010: learn: 0.2450488 total: 58.1s remaining: 517ms
1011: learn: 0.2450126 total: 58.2s remaining: 460ms
1012: learn: 0.2449923 total: 58.2s remaining: 402ms
1013: learn: 0.2449410 total: 58.3s remaining: 345ms
1014: learn: 0.2449186 total: 58.3s remaining: 287ms
1015: learn: 0.2448879 total: 58.4s remaining: 230ms
1016: learn: 0.2448202 total: 58.4s remaining: 172ms
1017: learn: 0.2447915 total: 58.5s remaining: 115ms
1018: learn: 0.2447693 total: 58.5s remaining: 57.5ms
1019: learn: 0.2447313 total: 58.6s remaining: 0us
Finished training fold 1 - running score 0.8608993902439024
Running fold 2, 15736 train samples, 2623 validation samples
0: learn: 0.6480601 total: 52ms remaining: 53s
1: learn: 0.6092785 total: 105ms remaining: 53.2s
2: learn: 0.5764557 total: 157ms remaining: 53.1s
3: learn: 0.5477072 total: 207ms remaining: 52.7s
4: learn: 0.5232115 total: 258ms remaining: 52.3s
5: learn: 0.5018042 total: 307ms remaining: 51.8s
6: learn: 0.4836158 total: 355ms remaining: 51.4s
7: learn: 0.4678372 total: 406ms remaining: 51.4s
8: learn: 0.4543365 total: 455ms remaining: 51.2s
9: learn: 0.4427095 total: 504ms remaining: 51s
10: learn: 0.4328145 total: 553ms remaining: 50.8s
11: learn: 0.4240927 total: 602ms remaining: 50.6s
12: learn: 0.4166116 total: 652ms remaining: 50.5s
13: learn: 0.4100681 total: 703ms remaining: 50.5s
14: learn: 0.4042198 total: 753ms remaining: 50.4s
15: learn: 0.3991623 total: 805ms remaining: 50.5s
16: learn: 0.3950794 total: 854ms remaining: 50.4s
17: learn: 0.3912594 total: 904ms remaining: 50.3s
18: learn: 0.3876887 total: 955ms remaining: 50.3s
19: learn: 0.3849004 total: 1s remaining: 50.3s
20: learn: 0.3823764 total: 1.05s remaining: 50.2s
21: learn: 0.3800247 total: 1.1s remaining: 50.1s
22: learn: 0.3778814 total: 1.15s remaining: 50s
23: learn: 0.3761041 total: 1.21s remaining: 50.1s
24: learn: 0.3744568 total: 1.26s remaining: 50s
25: learn: 0.3730224 total: 1.3s remaining: 49.9s
26: learn: 0.3718382 total: 1.35s remaining: 49.8s
27: learn: 0.3708757 total: 1.4s remaining: 49.7s
28: learn: 0.3699658 total: 1.45s remaining: 49.6s
29: learn: 0.3690812 total: 1.5s remaining: 49.5s
30: learn: 0.3682451 total: 1.55s remaining: 49.4s
31: learn: 0.3675831 total: 1.6s remaining: 49.3s
32: learn: 0.3668546 total: 1.65s remaining: 49.2s
33: learn: 0.3662519 total: 1.69s remaining: 49.1s
34: learn: 0.3657247 total: 1.74s remaining: 49.1s
35: learn: 0.3651335 total: 1.79s remaining: 49s
36: learn: 0.3647235 total: 1.84s remaining: 49s
37: learn: 0.3640634 total: 1.89s remaining: 48.9s
38: learn: 0.3636877 total: 1.94s remaining: 48.9s
39: learn: 0.3633547 total: 1.99s remaining: 48.8s
40: learn: 0.3630124 total: 2.04s remaining: 48.8s
41: learn: 0.3626953 total: 2.09s remaining: 48.7s
42: learn: 0.3622536 total: 2.14s remaining: 48.6s
43: learn: 0.3619401 total: 2.19s remaining: 48.5s
44: learn: 0.3615120 total: 2.24s remaining: 48.6s
45: learn: 0.3611915 total: 2.29s remaining: 48.5s
46: learn: 0.3608918 total: 2.34s remaining: 48.4s
47: learn: 0.3606207 total: 2.38s remaining: 48.3s
48: learn: 0.3602605 total: 2.43s remaining: 48.2s
49: learn: 0.3600771 total: 2.48s remaining: 48.1s
50: learn: 0.3597809 total: 2.53s remaining: 48.1s
51: learn: 0.3595514 total: 2.58s remaining: 48s
52: learn: 0.3593204 total: 2.63s remaining: 48.1s
53: learn: 0.3588635 total: 2.7s remaining: 48.3s
54: learn: 0.3587306 total: 2.76s remaining: 48.4s
55: learn: 0.3585420 total: 2.81s remaining: 48.5s
56: learn: 0.3583647 total: 2.88s remaining: 48.6s
57: learn: 0.3580290 total: 2.94s remaining: 48.8s
58: learn: 0.3578402 total: 3s remaining: 48.8s
59: learn: 0.3575649 total: 3.06s remaining: 48.9s
60: learn: 0.3573634 total: 3.12s remaining: 49s
61: learn: 0.3570598 total: 3.18s remaining: 49.2s
62: learn: 0.3570513 total: 3.21s remaining: 48.8s
63: learn: 0.3568952 total: 3.27s remaining: 48.8s
64: learn: 0.3565870 total: 3.34s remaining: 49s
65: learn: 0.3564405 total: 3.4s remaining: 49.1s
66: learn: 0.3561929 total: 3.46s remaining: 49.2s
67: learn: 0.3560397 total: 3.52s remaining: 49.3s
68: learn: 0.3557417 total: 3.58s remaining: 49.4s
69: learn: 0.3554381 total: 3.64s remaining: 49.5s
70: learn: 0.3551657 total: 3.71s remaining: 49.6s
71: learn: 0.3550218 total: 3.77s remaining: 49.6s
72: learn: 0.3548431 total: 3.83s remaining: 49.7s
73: learn: 0.3546228 total: 3.9s remaining: 49.8s
74: learn: 0.3545092 total: 3.96s remaining: 49.9s
75: learn: 0.3541867 total: 4.02s remaining: 50s
76: learn: 0.3539162 total: 4.08s remaining: 50s
77: learn: 0.3536613 total: 4.14s remaining: 50s
78: learn: 0.3535076 total: 4.2s remaining: 50.1s
79: learn: 0.3534022 total: 4.27s remaining: 50.1s
80: learn: 0.3530865 total: 4.33s remaining: 50.1s
81: learn: 0.3528168 total: 4.39s remaining: 50.2s
82: learn: 0.3526367 total: 4.45s remaining: 50.3s
83: learn: 0.3523360 total: 4.51s remaining: 50.3s
84: learn: 0.3521576 total: 4.58s remaining: 50.3s
85: learn: 0.3518371 total: 4.64s remaining: 50.4s
86: learn: 0.3516523 total: 4.7s remaining: 50.4s
87: learn: 0.3515269 total: 4.75s remaining: 50.3s
88: learn: 0.3513405 total: 4.82s remaining: 50.4s
89: learn: 0.3510531 total: 4.88s remaining: 50.4s
90: learn: 0.3505301 total: 4.94s remaining: 50.4s
91: learn: 0.3502289 total: 5s remaining: 50.5s
92: learn: 0.3498451 total: 5.07s remaining: 50.5s
93: learn: 0.3496441 total: 5.13s remaining: 50.5s
94: learn: 0.3494586 total: 5.19s remaining: 50.5s
95: learn: 0.3492638 total: 5.25s remaining: 50.5s
96: learn: 0.3491305 total: 5.31s remaining: 50.5s
97: learn: 0.3489878 total: 5.37s remaining: 50.5s
98: learn: 0.3489151 total: 5.41s remaining: 50.3s
99: learn: 0.3487205 total: 5.47s remaining: 50.3s
100: learn: 0.3485919 total: 5.54s remaining: 50.4s
101: learn: 0.3484584 total: 5.6s remaining: 50.4s
102: learn: 0.3483557 total: 5.66s remaining: 50.4s
103: learn: 0.3482307 total: 5.72s remaining: 50.4s
104: learn: 0.3480604 total: 5.79s remaining: 50.4s
105: learn: 0.3478883 total: 5.85s remaining: 50.4s
106: learn: 0.3477339 total: 5.91s remaining: 50.4s
107: learn: 0.3473594 total: 5.97s remaining: 50.4s
108: learn: 0.3470281 total: 6.03s remaining: 50.4s
109: learn: 0.3468167 total: 6.08s remaining: 50.3s
110: learn: 0.3466801 total: 6.13s remaining: 50.2s
111: learn: 0.3465184 total: 6.18s remaining: 50.1s
112: learn: 0.3463866 total: 6.23s remaining: 50s
113: learn: 0.3461559 total: 6.28s remaining: 49.9s
114: learn: 0.3459473 total: 6.33s remaining: 49.8s
115: learn: 0.3457162 total: 6.38s remaining: 49.7s
116: learn: 0.3455255 total: 6.43s remaining: 49.7s
117: learn: 0.3453564 total: 6.48s remaining: 49.6s
118: learn: 0.3451619 total: 6.54s remaining: 49.5s
119: learn: 0.3450447 total: 6.59s remaining: 49.4s
120: learn: 0.3448355 total: 6.64s remaining: 49.4s
121: learn: 0.3446249 total: 6.69s remaining: 49.3s
122: learn: 0.3443862 total: 6.74s remaining: 49.2s
123: learn: 0.3440992 total: 6.79s remaining: 49.1s
124: learn: 0.3439776 total: 6.84s remaining: 49s
125: learn: 0.3438430 total: 6.89s remaining: 48.9s
126: learn: 0.3437439 total: 6.95s remaining: 48.8s
127: learn: 0.3434396 total: 7s remaining: 48.8s
128: learn: 0.3433132 total: 7.05s remaining: 48.7s
129: learn: 0.3430763 total: 7.1s remaining: 48.6s
130: learn: 0.3427751 total: 7.16s remaining: 48.6s
131: learn: 0.3426100 total: 7.21s remaining: 48.5s
132: learn: 0.3424505 total: 7.25s remaining: 48.4s
133: learn: 0.3422964 total: 7.31s remaining: 48.3s
134: learn: 0.3420979 total: 7.36s remaining: 48.2s
135: learn: 0.3419448 total: 7.41s remaining: 48.2s
136: learn: 0.3417311 total: 7.46s remaining: 48.1s
137: learn: 0.3416064 total: 7.51s remaining: 48s
138: learn: 0.3413039 total: 7.57s remaining: 48s
139: learn: 0.3411044 total: 7.62s remaining: 47.9s
140: learn: 0.3410128 total: 7.67s remaining: 47.8s
141: learn: 0.3407947 total: 7.72s remaining: 47.8s
142: learn: 0.3406988 total: 7.77s remaining: 47.7s
143: learn: 0.3406083 total: 7.82s remaining: 47.6s
144: learn: 0.3404726 total: 7.87s remaining: 47.5s
145: learn: 0.3402954 total: 7.92s remaining: 47.4s
146: learn: 0.3400267 total: 7.97s remaining: 47.4s
147: learn: 0.3397054 total: 8.03s remaining: 47.3s
148: learn: 0.3395022 total: 8.08s remaining: 47.2s
149: learn: 0.3392460 total: 8.13s remaining: 47.2s
150: learn: 0.3390869 total: 8.18s remaining: 47.1s
151: learn: 0.3389514 total: 8.23s remaining: 47s
152: learn: 0.3388531 total: 8.28s remaining: 46.9s
153: learn: 0.3385867 total: 8.34s remaining: 46.9s
154: learn: 0.3385095 total: 8.39s remaining: 46.8s
155: learn: 0.3383555 total: 8.44s remaining: 46.7s
156: learn: 0.3381258 total: 8.49s remaining: 46.7s
157: learn: 0.3379796 total: 8.54s remaining: 46.6s
158: learn: 0.3377207 total: 8.59s remaining: 46.5s
159: learn: 0.3375306 total: 8.64s remaining: 46.5s
160: learn: 0.3373851 total: 8.7s remaining: 46.4s
161: learn: 0.3370182 total: 8.75s remaining: 46.4s
162: learn: 0.3368464 total: 8.8s remaining: 46.3s
163: learn: 0.3367301 total: 8.85s remaining: 46.2s
164: learn: 0.3365948 total: 8.9s remaining: 46.1s
165: learn: 0.3364371 total: 8.95s remaining: 46.1s
166: learn: 0.3363016 total: 9s remaining: 46s
167: learn: 0.3360215 total: 9.05s remaining: 45.9s
168: learn: 0.3358754 total: 9.1s remaining: 45.8s
169: learn: 0.3357363 total: 9.16s remaining: 45.8s
170: learn: 0.3355012 total: 9.21s remaining: 45.7s
171: learn: 0.3353638 total: 9.26s remaining: 45.6s
172: learn: 0.3351941 total: 9.3s remaining: 45.6s
173: learn: 0.3350455 total: 9.35s remaining: 45.5s
174: learn: 0.3347758 total: 9.4s remaining: 45.4s
175: learn: 0.3344503 total: 9.46s remaining: 45.3s
176: learn: 0.3343425 total: 9.52s remaining: 45.3s
177: learn: 0.3340968 total: 9.58s remaining: 45.3s
178: learn: 0.3339373 total: 9.64s remaining: 45.3s
179: learn: 0.3337362 total: 9.7s remaining: 45.3s
180: learn: 0.3336442 total: 9.77s remaining: 45.3s
181: learn: 0.3334499 total: 9.83s remaining: 45.3s
182: learn: 0.3331778 total: 9.89s remaining: 45.3s
183: learn: 0.3329456 total: 9.96s remaining: 45.2s
184: learn: 0.3327553 total: 10s remaining: 45.2s
185: learn: 0.3326117 total: 10.1s remaining: 45.2s
186: learn: 0.3324414 total: 10.1s remaining: 45.2s
187: learn: 0.3322558 total: 10.2s remaining: 45.2s
188: learn: 0.3319765 total: 10.3s remaining: 45.1s
189: learn: 0.3314847 total: 10.3s remaining: 45.1s
190: learn: 0.3313214 total: 10.4s remaining: 45.1s
191: learn: 0.3310848 total: 10.4s remaining: 45.1s
192: learn: 0.3308304 total: 10.5s remaining: 45s
193: learn: 0.3305541 total: 10.6s remaining: 45s
194: learn: 0.3304004 total: 10.6s remaining: 45s
195: learn: 0.3302799 total: 10.7s remaining: 44.9s
196: learn: 0.3301382 total: 10.8s remaining: 44.9s
197: learn: 0.3300179 total: 10.8s remaining: 44.9s
198: learn: 0.3298201 total: 10.9s remaining: 44.9s
199: learn: 0.3295737 total: 10.9s remaining: 44.8s
200: learn: 0.3294912 total: 11s remaining: 44.8s
201: learn: 0.3291321 total: 11.1s remaining: 44.8s
202: learn: 0.3288611 total: 11.1s remaining: 44.8s
203: learn: 0.3287371 total: 11.2s remaining: 44.7s
204: learn: 0.3284346 total: 11.2s remaining: 44.7s
205: learn: 0.3282773 total: 11.3s remaining: 44.7s
206: learn: 0.3280939 total: 11.4s remaining: 44.7s
207: learn: 0.3279591 total: 11.4s remaining: 44.6s
208: learn: 0.3277199 total: 11.5s remaining: 44.6s
209: learn: 0.3275314 total: 11.6s remaining: 44.6s
210: learn: 0.3273497 total: 11.6s remaining: 44.5s
211: learn: 0.3272363 total: 11.7s remaining: 44.5s
212: learn: 0.3270726 total: 11.7s remaining: 44.5s
213: learn: 0.3268436 total: 11.8s remaining: 44.4s
214: learn: 0.3265591 total: 11.9s remaining: 44.4s
215: learn: 0.3264552 total: 11.9s remaining: 44.4s
216: learn: 0.3262937 total: 12s remaining: 44.4s
217: learn: 0.3261887 total: 12s remaining: 44.3s
218: learn: 0.3259872 total: 12.1s remaining: 44.3s
219: learn: 0.3258435 total: 12.2s remaining: 44.3s
220: learn: 0.3257038 total: 12.2s remaining: 44.3s
221: learn: 0.3255208 total: 12.3s remaining: 44.2s
222: learn: 0.3253612 total: 12.4s remaining: 44.2s
223: learn: 0.3251382 total: 12.4s remaining: 44.2s
224: learn: 0.3248729 total: 12.5s remaining: 44.1s
225: learn: 0.3246710 total: 12.6s remaining: 44.1s
226: learn: 0.3245173 total: 12.6s remaining: 44.1s
227: learn: 0.3243089 total: 12.7s remaining: 44s
228: learn: 0.3241310 total: 12.7s remaining: 44s
229: learn: 0.3239085 total: 12.8s remaining: 44s
230: learn: 0.3237425 total: 12.9s remaining: 43.9s
231: learn: 0.3235744 total: 12.9s remaining: 43.9s
232: learn: 0.3233192 total: 13s remaining: 43.8s
233: learn: 0.3231237 total: 13s remaining: 43.8s
234: learn: 0.3229299 total: 13.1s remaining: 43.7s
235: learn: 0.3227753 total: 13.1s remaining: 43.6s
236: learn: 0.3226695 total: 13.2s remaining: 43.5s
237: learn: 0.3223883 total: 13.2s remaining: 43.5s
238: learn: 0.3221888 total: 13.3s remaining: 43.4s
239: learn: 0.3217529 total: 13.3s remaining: 43.3s
240: learn: 0.3214412 total: 13.4s remaining: 43.3s
241: learn: 0.3212899 total: 13.4s remaining: 43.2s
242: learn: 0.3210734 total: 13.5s remaining: 43.1s
243: learn: 0.3208729 total: 13.5s remaining: 43s
244: learn: 0.3203940 total: 13.6s remaining: 43s
245: learn: 0.3201758 total: 13.6s remaining: 42.9s
246: learn: 0.3199735 total: 13.7s remaining: 42.8s
247: learn: 0.3198256 total: 13.7s remaining: 42.8s
248: learn: 0.3197146 total: 13.8s remaining: 42.7s
249: learn: 0.3194911 total: 13.8s remaining: 42.6s
250: learn: 0.3192914 total: 13.9s remaining: 42.5s
251: learn: 0.3191597 total: 13.9s remaining: 42.5s
252: learn: 0.3187844 total: 14s remaining: 42.4s
253: learn: 0.3186454 total: 14s remaining: 42.3s
254: learn: 0.3184764 total: 14.1s remaining: 42.3s
255: learn: 0.3182773 total: 14.1s remaining: 42.2s
256: learn: 0.3178885 total: 14.2s remaining: 42.1s
257: learn: 0.3175453 total: 14.2s remaining: 42.1s
258: learn: 0.3173949 total: 14.3s remaining: 42s
259: learn: 0.3171493 total: 14.4s remaining: 42s
260: learn: 0.3169766 total: 14.4s remaining: 41.9s
261: learn: 0.3167388 total: 14.5s remaining: 41.8s
262: learn: 0.3165280 total: 14.5s remaining: 41.7s
263: learn: 0.3163168 total: 14.5s remaining: 41.7s
264: learn: 0.3160475 total: 14.6s remaining: 41.6s
265: learn: 0.3157300 total: 14.7s remaining: 41.5s
266: learn: 0.3155409 total: 14.7s remaining: 41.5s
267: learn: 0.3154785 total: 14.7s remaining: 41.4s
268: learn: 0.3153607 total: 14.8s remaining: 41.3s
269: learn: 0.3152337 total: 14.8s remaining: 41.2s
270: learn: 0.3149551 total: 14.9s remaining: 41.2s
271: learn: 0.3148639 total: 14.9s remaining: 41.1s
272: learn: 0.3146407 total: 15s remaining: 41s
273: learn: 0.3145388 total: 15s remaining: 41s
274: learn: 0.3143798 total: 15.1s remaining: 40.9s
275: learn: 0.3142270 total: 15.1s remaining: 40.8s
276: learn: 0.3141011 total: 15.2s remaining: 40.8s
277: learn: 0.3139410 total: 15.2s remaining: 40.7s
278: learn: 0.3137477 total: 15.3s remaining: 40.6s
279: learn: 0.3136251 total: 15.4s remaining: 40.6s
280: learn: 0.3135032 total: 15.4s remaining: 40.5s
281: learn: 0.3133623 total: 15.5s remaining: 40.5s
282: learn: 0.3131803 total: 15.5s remaining: 40.4s
283: learn: 0.3130250 total: 15.6s remaining: 40.3s
284: learn: 0.3128382 total: 15.6s remaining: 40.3s
285: learn: 0.3127190 total: 15.7s remaining: 40.2s
286: learn: 0.3125257 total: 15.7s remaining: 40.1s
287: learn: 0.3124153 total: 15.8s remaining: 40.1s
288: learn: 0.3122856 total: 15.8s remaining: 40s
289: learn: 0.3119756 total: 15.9s remaining: 39.9s
290: learn: 0.3118508 total: 15.9s remaining: 39.9s
291: learn: 0.3116922 total: 16s remaining: 39.8s
292: learn: 0.3115164 total: 16s remaining: 39.7s
293: learn: 0.3114401 total: 16.1s remaining: 39.7s
294: learn: 0.3112419 total: 16.1s remaining: 39.6s
295: learn: 0.3110806 total: 16.2s remaining: 39.5s
296: learn: 0.3108934 total: 16.2s remaining: 39.5s
297: learn: 0.3107725 total: 16.3s remaining: 39.4s
298: learn: 0.3106378 total: 16.3s remaining: 39.4s
299: learn: 0.3103976 total: 16.4s remaining: 39.3s
300: learn: 0.3102125 total: 16.5s remaining: 39.3s
301: learn: 0.3100755 total: 16.5s remaining: 39.3s
302: learn: 0.3099800 total: 16.6s remaining: 39.2s
303: learn: 0.3098060 total: 16.6s remaining: 39.2s
304: learn: 0.3095949 total: 16.7s remaining: 39.1s
305: learn: 0.3094677 total: 16.8s remaining: 39.1s
306: learn: 0.3092125 total: 16.8s remaining: 39.1s
307: learn: 0.3091461 total: 16.9s remaining: 39s
308: learn: 0.3089975 total: 16.9s remaining: 39s
309: learn: 0.3087626 total: 17s remaining: 38.9s
310: learn: 0.3086453 total: 17.1s remaining: 38.9s
311: learn: 0.3085516 total: 17.1s remaining: 38.9s
312: learn: 0.3083981 total: 17.2s remaining: 38.8s
313: learn: 0.3082194 total: 17.3s remaining: 38.8s
314: learn: 0.3081330 total: 17.3s remaining: 38.8s
315: learn: 0.3079241 total: 17.4s remaining: 38.7s
316: learn: 0.3076359 total: 17.4s remaining: 38.7s
317: learn: 0.3074850 total: 17.5s remaining: 38.6s
318: learn: 0.3073333 total: 17.6s remaining: 38.6s
319: learn: 0.3069931 total: 17.6s remaining: 38.6s
320: learn: 0.3068667 total: 17.7s remaining: 38.5s
321: learn: 0.3067749 total: 17.8s remaining: 38.5s
322: learn: 0.3067747 total: 17.8s remaining: 38.4s
323: learn: 0.3066026 total: 17.8s remaining: 38.3s
324: learn: 0.3063031 total: 17.9s remaining: 38.3s
325: learn: 0.3061946 total: 18s remaining: 38.2s
326: learn: 0.3058605 total: 18s remaining: 38.2s
327: learn: 0.3056376 total: 18.1s remaining: 38.2s
328: learn: 0.3055234 total: 18.1s remaining: 38.1s
329: learn: 0.3051826 total: 18.2s remaining: 38.1s
330: learn: 0.3050266 total: 18.3s remaining: 38s
331: learn: 0.3049214 total: 18.3s remaining: 38s
332: learn: 0.3048081 total: 18.4s remaining: 38s
333: learn: 0.3046378 total: 18.5s remaining: 37.9s
334: learn: 0.3045016 total: 18.5s remaining: 37.9s
335: learn: 0.3044453 total: 18.6s remaining: 37.8s
336: learn: 0.3043379 total: 18.6s remaining: 37.8s
337: learn: 0.3041790 total: 18.7s remaining: 37.7s
338: learn: 0.3039288 total: 18.8s remaining: 37.7s
339: learn: 0.3037474 total: 18.8s remaining: 37.7s
340: learn: 0.3035451 total: 18.9s remaining: 37.6s
341: learn: 0.3033910 total: 19s remaining: 37.6s
342: learn: 0.3033058 total: 19s remaining: 37.5s
343: learn: 0.3032284 total: 19.1s remaining: 37.5s
344: learn: 0.3031543 total: 19.1s remaining: 37.4s
345: learn: 0.3030150 total: 19.2s remaining: 37.4s
346: learn: 0.3029199 total: 19.3s remaining: 37.4s
347: learn: 0.3027823 total: 19.3s remaining: 37.3s
348: learn: 0.3026935 total: 19.4s remaining: 37.3s
349: learn: 0.3025397 total: 19.4s remaining: 37.2s
350: learn: 0.3024336 total: 19.5s remaining: 37.2s
351: learn: 0.3022840 total: 19.6s remaining: 37.2s
352: learn: 0.3020636 total: 19.6s remaining: 37.1s
353: learn: 0.3019880 total: 19.7s remaining: 37.1s
354: learn: 0.3019104 total: 19.8s remaining: 37s
355: learn: 0.3017769 total: 19.8s remaining: 36.9s
356: learn: 0.3016662 total: 19.9s remaining: 36.9s
357: learn: 0.3015621 total: 19.9s remaining: 36.8s
358: learn: 0.3014520 total: 20s remaining: 36.8s
359: learn: 0.3013714 total: 20s remaining: 36.7s
360: learn: 0.3012657 total: 20.1s remaining: 36.6s
361: learn: 0.3011564 total: 20.1s remaining: 36.6s
362: learn: 0.3010303 total: 20.2s remaining: 36.5s
363: learn: 0.3009031 total: 20.2s remaining: 36.4s
364: learn: 0.3007664 total: 20.3s remaining: 36.4s
365: learn: 0.3006231 total: 20.3s remaining: 36.3s
366: learn: 0.3005007 total: 20.4s remaining: 36.2s
367: learn: 0.3004357 total: 20.4s remaining: 36.2s
368: learn: 0.3002376 total: 20.5s remaining: 36.1s
369: learn: 0.3001282 total: 20.5s remaining: 36s
370: learn: 0.2999972 total: 20.6s remaining: 36s
371: learn: 0.2999712 total: 20.6s remaining: 35.9s
372: learn: 0.2998393 total: 20.6s remaining: 35.8s
373: learn: 0.2996756 total: 20.7s remaining: 35.8s
374: learn: 0.2995202 total: 20.8s remaining: 35.7s
375: learn: 0.2992404 total: 20.8s remaining: 35.6s
376: learn: 0.2990699 total: 20.9s remaining: 35.6s
377: learn: 0.2989658 total: 20.9s remaining: 35.5s
378: learn: 0.2988092 total: 21s remaining: 35.4s
379: learn: 0.2986921 total: 21s remaining: 35.4s
380: learn: 0.2985478 total: 21.1s remaining: 35.3s
381: learn: 0.2984309 total: 21.1s remaining: 35.3s
382: learn: 0.2982288 total: 21.2s remaining: 35.2s
383: learn: 0.2981392 total: 21.2s remaining: 35.1s
384: learn: 0.2980485 total: 21.3s remaining: 35.1s
385: learn: 0.2979113 total: 21.3s remaining: 35s
386: learn: 0.2978155 total: 21.4s remaining: 34.9s
387: learn: 0.2975796 total: 21.4s remaining: 34.9s
388: learn: 0.2973075 total: 21.5s remaining: 34.8s
389: learn: 0.2970912 total: 21.5s remaining: 34.8s
390: learn: 0.2970271 total: 21.6s remaining: 34.7s
391: learn: 0.2968728 total: 21.6s remaining: 34.6s
392: learn: 0.2967542 total: 21.7s remaining: 34.6s
393: learn: 0.2965147 total: 21.7s remaining: 34.5s
394: learn: 0.2964455 total: 21.8s remaining: 34.5s
395: learn: 0.2963003 total: 21.8s remaining: 34.4s
396: learn: 0.2960178 total: 21.9s remaining: 34.3s
397: learn: 0.2958932 total: 21.9s remaining: 34.3s
398: learn: 0.2957200 total: 22s remaining: 34.2s
399: learn: 0.2955504 total: 22s remaining: 34.1s
400: learn: 0.2955043 total: 22.1s remaining: 34.1s
401: learn: 0.2954231 total: 22.1s remaining: 34s
402: learn: 0.2953435 total: 22.2s remaining: 34s
403: learn: 0.2950835 total: 22.2s remaining: 33.9s
404: learn: 0.2949615 total: 22.3s remaining: 33.8s
405: learn: 0.2948483 total: 22.3s remaining: 33.8s
406: learn: 0.2947987 total: 22.4s remaining: 33.7s
407: learn: 0.2946830 total: 22.4s remaining: 33.7s
408: learn: 0.2945595 total: 22.5s remaining: 33.6s
409: learn: 0.2944729 total: 22.5s remaining: 33.5s
410: learn: 0.2944123 total: 22.6s remaining: 33.5s
411: learn: 0.2943163 total: 22.6s remaining: 33.4s
412: learn: 0.2941131 total: 22.7s remaining: 33.3s
413: learn: 0.2939453 total: 22.7s remaining: 33.3s
414: learn: 0.2937460 total: 22.8s remaining: 33.2s
415: learn: 0.2936203 total: 22.8s remaining: 33.1s
416: learn: 0.2934383 total: 22.9s remaining: 33.1s
417: learn: 0.2931626 total: 22.9s remaining: 33s
418: learn: 0.2930523 total: 23s remaining: 33s
419: learn: 0.2929421 total: 23s remaining: 32.9s
420: learn: 0.2927629 total: 23.1s remaining: 32.9s
421: learn: 0.2925357 total: 23.1s remaining: 32.8s
422: learn: 0.2924285 total: 23.2s remaining: 32.7s
423: learn: 0.2922770 total: 23.3s remaining: 32.7s
424: learn: 0.2920551 total: 23.3s remaining: 32.6s
425: learn: 0.2919664 total: 23.4s remaining: 32.6s
426: learn: 0.2919018 total: 23.4s remaining: 32.6s
427: learn: 0.2916864 total: 23.5s remaining: 32.5s
428: learn: 0.2916159 total: 23.6s remaining: 32.5s
429: learn: 0.2914732 total: 23.6s remaining: 32.4s
430: learn: 0.2913982 total: 23.7s remaining: 32.4s
431: learn: 0.2913481 total: 23.8s remaining: 32.3s
432: learn: 0.2912732 total: 23.8s remaining: 32.3s
433: learn: 0.2910028 total: 23.9s remaining: 32.2s
434: learn: 0.2908740 total: 23.9s remaining: 32.2s
435: learn: 0.2907152 total: 24s remaining: 32.2s
436: learn: 0.2905962 total: 24.1s remaining: 32.1s
437: learn: 0.2903781 total: 24.1s remaining: 32.1s
438: learn: 0.2901551 total: 24.2s remaining: 32s
439: learn: 0.2900972 total: 24.2s remaining: 32s
440: learn: 0.2899835 total: 24.3s remaining: 31.9s
441: learn: 0.2899261 total: 24.4s remaining: 31.9s
442: learn: 0.2898515 total: 24.4s remaining: 31.8s
443: learn: 0.2897606 total: 24.5s remaining: 31.8s
444: learn: 0.2895949 total: 24.6s remaining: 31.7s
445: learn: 0.2894734 total: 24.6s remaining: 31.7s
446: learn: 0.2892318 total: 24.7s remaining: 31.7s
447: learn: 0.2890243 total: 24.8s remaining: 31.6s
448: learn: 0.2889437 total: 24.8s remaining: 31.6s
449: learn: 0.2888753 total: 24.9s remaining: 31.5s
450: learn: 0.2888078 total: 24.9s remaining: 31.5s
451: learn: 0.2887354 total: 25s remaining: 31.4s
452: learn: 0.2886049 total: 25.1s remaining: 31.4s
453: learn: 0.2884753 total: 25.1s remaining: 31.3s
454: learn: 0.2883978 total: 25.2s remaining: 31.3s
455: learn: 0.2882493 total: 25.2s remaining: 31.2s
456: learn: 0.2881544 total: 25.3s remaining: 31.2s
457: learn: 0.2880582 total: 25.4s remaining: 31.1s
458: learn: 0.2879255 total: 25.4s remaining: 31.1s
459: learn: 0.2877643 total: 25.5s remaining: 31s
460: learn: 0.2875142 total: 25.6s remaining: 31s
461: learn: 0.2873283 total: 25.6s remaining: 30.9s
462: learn: 0.2870403 total: 25.7s remaining: 30.9s
463: learn: 0.2869225 total: 25.7s remaining: 30.9s
464: learn: 0.2868099 total: 25.8s remaining: 30.8s
465: learn: 0.2866460 total: 25.9s remaining: 30.8s
466: learn: 0.2865719 total: 25.9s remaining: 30.7s
467: learn: 0.2863781 total: 26s remaining: 30.7s
468: learn: 0.2863492 total: 26.1s remaining: 30.6s
469: learn: 0.2862294 total: 26.1s remaining: 30.6s
470: learn: 0.2858395 total: 26.2s remaining: 30.5s
471: learn: 0.2856335 total: 26.2s remaining: 30.5s
472: learn: 0.2854758 total: 26.3s remaining: 30.4s
473: learn: 0.2853556 total: 26.4s remaining: 30.4s
474: learn: 0.2852248 total: 26.4s remaining: 30.3s
475: learn: 0.2850946 total: 26.5s remaining: 30.3s
476: learn: 0.2849902 total: 26.6s remaining: 30.2s
477: learn: 0.2849054 total: 26.6s remaining: 30.2s
478: learn: 0.2847949 total: 26.7s remaining: 30.1s
479: learn: 0.2847264 total: 26.7s remaining: 30.1s
480: learn: 0.2846120 total: 26.8s remaining: 30s
481: learn: 0.2845259 total: 26.8s remaining: 30s
482: learn: 0.2844708 total: 26.9s remaining: 29.9s
483: learn: 0.2844351 total: 26.9s remaining: 29.8s
484: learn: 0.2843871 total: 27s remaining: 29.8s
485: learn: 0.2842647 total: 27s remaining: 29.7s
486: learn: 0.2842056 total: 27.1s remaining: 29.6s
487: learn: 0.2841618 total: 27.1s remaining: 29.6s
488: learn: 0.2840596 total: 27.2s remaining: 29.5s
489: learn: 0.2840054 total: 27.2s remaining: 29.5s
490: learn: 0.2838631 total: 27.3s remaining: 29.4s
491: learn: 0.2837666 total: 27.3s remaining: 29.3s
492: learn: 0.2837110 total: 27.4s remaining: 29.3s
493: learn: 0.2835439 total: 27.4s remaining: 29.2s
494: learn: 0.2833890 total: 27.5s remaining: 29.2s
495: learn: 0.2832722 total: 27.6s remaining: 29.1s
496: learn: 0.2831086 total: 27.6s remaining: 29s
497: learn: 0.2829710 total: 27.6s remaining: 29s
498: learn: 0.2829464 total: 27.7s remaining: 28.9s
499: learn: 0.2827654 total: 27.8s remaining: 28.9s
500: learn: 0.2826319 total: 27.8s remaining: 28.8s
501: learn: 0.2824989 total: 27.9s remaining: 28.7s
502: learn: 0.2822416 total: 27.9s remaining: 28.7s
503: learn: 0.2821558 total: 28s remaining: 28.6s
504: learn: 0.2819828 total: 28s remaining: 28.6s
505: learn: 0.2818967 total: 28.1s remaining: 28.5s
506: learn: 0.2818376 total: 28.1s remaining: 28.4s
507: learn: 0.2817356 total: 28.2s remaining: 28.4s
508: learn: 0.2815994 total: 28.2s remaining: 28.3s
509: learn: 0.2815504 total: 28.3s remaining: 28.3s
510: learn: 0.2814219 total: 28.3s remaining: 28.2s
511: learn: 0.2812196 total: 28.3s remaining: 28.1s
512: learn: 0.2810038 total: 28.4s remaining: 28.1s
513: learn: 0.2809129 total: 28.4s remaining: 28s
514: learn: 0.2808562 total: 28.5s remaining: 27.9s
515: learn: 0.2807211 total: 28.5s remaining: 27.9s
516: learn: 0.2806391 total: 28.6s remaining: 27.8s
517: learn: 0.2805116 total: 28.6s remaining: 27.8s
518: learn: 0.2804327 total: 28.7s remaining: 27.7s
519: learn: 0.2802648 total: 28.8s remaining: 27.6s
520: learn: 0.2802286 total: 28.8s remaining: 27.6s
521: learn: 0.2801735 total: 28.9s remaining: 27.5s
522: learn: 0.2800860 total: 28.9s remaining: 27.5s
523: learn: 0.2799878 total: 29s remaining: 27.4s
524: learn: 0.2799064 total: 29s remaining: 27.4s
525: learn: 0.2799063 total: 29s remaining: 27.3s
526: learn: 0.2798083 total: 29.1s remaining: 27.2s
527: learn: 0.2798078 total: 29.1s remaining: 27.1s
528: learn: 0.2798078 total: 29.1s remaining: 27s
529: learn: 0.2797480 total: 29.2s remaining: 27s
530: learn: 0.2797261 total: 29.2s remaining: 26.9s
531: learn: 0.2796423 total: 29.3s remaining: 26.9s
532: learn: 0.2795964 total: 29.3s remaining: 26.8s
533: learn: 0.2795964 total: 29.3s remaining: 26.7s
534: learn: 0.2795957 total: 29.4s remaining: 26.6s
535: learn: 0.2794476 total: 29.4s remaining: 26.6s
536: learn: 0.2793008 total: 29.5s remaining: 26.5s
537: learn: 0.2790818 total: 29.5s remaining: 26.4s
538: learn: 0.2790818 total: 29.5s remaining: 26.4s
539: learn: 0.2789210 total: 29.6s remaining: 26.3s
540: learn: 0.2788147 total: 29.6s remaining: 26.2s
541: learn: 0.2787371 total: 29.7s remaining: 26.2s
542: learn: 0.2786717 total: 29.7s remaining: 26.1s
543: learn: 0.2786103 total: 29.8s remaining: 26.1s
544: learn: 0.2785153 total: 29.9s remaining: 26s
545: learn: 0.2784711 total: 29.9s remaining: 26s
546: learn: 0.2784016 total: 30s remaining: 25.9s
547: learn: 0.2783431 total: 30s remaining: 25.8s
548: learn: 0.2783430 total: 30s remaining: 25.8s
549: learn: 0.2781455 total: 30.1s remaining: 25.7s
550: learn: 0.2780759 total: 30.1s remaining: 25.7s
551: learn: 0.2779708 total: 30.2s remaining: 25.6s
552: learn: 0.2778712 total: 30.3s remaining: 25.6s
553: learn: 0.2777218 total: 30.3s remaining: 25.5s
554: learn: 0.2775102 total: 30.4s remaining: 25.5s
555: learn: 0.2773936 total: 30.5s remaining: 25.4s
556: learn: 0.2773382 total: 30.5s remaining: 25.4s
557: learn: 0.2772120 total: 30.6s remaining: 25.3s
558: learn: 0.2770243 total: 30.6s remaining: 25.3s
559: learn: 0.2769505 total: 30.7s remaining: 25.2s
560: learn: 0.2768554 total: 30.8s remaining: 25.2s
561: learn: 0.2767529 total: 30.8s remaining: 25.1s
562: learn: 0.2766686 total: 30.9s remaining: 25.1s
563: learn: 0.2765192 total: 31s remaining: 25s
564: learn: 0.2764190 total: 31s remaining: 25s
565: learn: 0.2763892 total: 31.1s remaining: 24.9s
566: learn: 0.2763258 total: 31.1s remaining: 24.9s
567: learn: 0.2762806 total: 31.2s remaining: 24.8s
568: learn: 0.2761750 total: 31.3s remaining: 24.8s
569: learn: 0.2761101 total: 31.3s remaining: 24.7s
570: learn: 0.2760471 total: 31.4s remaining: 24.7s
571: learn: 0.2758819 total: 31.4s remaining: 24.6s
572: learn: 0.2758278 total: 31.5s remaining: 24.6s
573: learn: 0.2756746 total: 31.6s remaining: 24.5s
574: learn: 0.2755303 total: 31.6s remaining: 24.5s
575: learn: 0.2754657 total: 31.7s remaining: 24.4s
576: learn: 0.2754655 total: 31.7s remaining: 24.4s
577: learn: 0.2753023 total: 31.8s remaining: 24.3s
578: learn: 0.2751781 total: 31.8s remaining: 24.3s
579: learn: 0.2751230 total: 31.9s remaining: 24.2s
580: learn: 0.2750387 total: 32s remaining: 24.2s
581: learn: 0.2749782 total: 32s remaining: 24.1s
582: learn: 0.2748298 total: 32.1s remaining: 24.1s
583: learn: 0.2747669 total: 32.1s remaining: 24s
584: learn: 0.2746894 total: 32.2s remaining: 23.9s
585: learn: 0.2746074 total: 32.3s remaining: 23.9s
586: learn: 0.2745766 total: 32.3s remaining: 23.8s
587: learn: 0.2745244 total: 32.4s remaining: 23.8s
588: learn: 0.2744621 total: 32.4s remaining: 23.7s
589: learn: 0.2743335 total: 32.5s remaining: 23.7s
590: learn: 0.2742919 total: 32.6s remaining: 23.6s
591: learn: 0.2739454 total: 32.6s remaining: 23.6s
592: learn: 0.2739005 total: 32.7s remaining: 23.5s
593: learn: 0.2737900 total: 32.8s remaining: 23.5s
594: learn: 0.2736711 total: 32.8s remaining: 23.4s
595: learn: 0.2735087 total: 32.9s remaining: 23.4s
596: learn: 0.2734140 total: 32.9s remaining: 23.3s
597: learn: 0.2732583 total: 33s remaining: 23.3s
598: learn: 0.2731188 total: 33.1s remaining: 23.2s
599: learn: 0.2730428 total: 33.1s remaining: 23.2s
600: learn: 0.2730032 total: 33.2s remaining: 23.1s
601: learn: 0.2728525 total: 33.3s remaining: 23.1s
602: learn: 0.2727868 total: 33.3s remaining: 23s
603: learn: 0.2726544 total: 33.4s remaining: 23s
604: learn: 0.2725695 total: 33.4s remaining: 22.9s
605: learn: 0.2725038 total: 33.5s remaining: 22.9s
606: learn: 0.2724323 total: 33.5s remaining: 22.8s
607: learn: 0.2723120 total: 33.6s remaining: 22.8s
608: learn: 0.2721694 total: 33.6s remaining: 22.7s
609: learn: 0.2720798 total: 33.7s remaining: 22.6s
610: learn: 0.2719837 total: 33.7s remaining: 22.6s
611: learn: 0.2719397 total: 33.8s remaining: 22.5s
612: learn: 0.2718874 total: 33.8s remaining: 22.5s
613: learn: 0.2718380 total: 33.9s remaining: 22.4s
614: learn: 0.2717827 total: 33.9s remaining: 22.3s
615: learn: 0.2717117 total: 34s remaining: 22.3s
616: learn: 0.2715758 total: 34s remaining: 22.2s
617: learn: 0.2715732 total: 34.1s remaining: 22.2s
618: learn: 0.2714916 total: 34.1s remaining: 22.1s
619: learn: 0.2713072 total: 34.2s remaining: 22s
620: learn: 0.2712643 total: 34.2s remaining: 22s
621: learn: 0.2711885 total: 34.3s remaining: 21.9s
622: learn: 0.2711494 total: 34.3s remaining: 21.9s
623: learn: 0.2708548 total: 34.4s remaining: 21.8s
624: learn: 0.2707779 total: 34.4s remaining: 21.8s
625: learn: 0.2707412 total: 34.5s remaining: 21.7s
626: learn: 0.2706013 total: 34.5s remaining: 21.6s
627: learn: 0.2705773 total: 34.6s remaining: 21.6s
628: learn: 0.2704855 total: 34.6s remaining: 21.5s
629: learn: 0.2703993 total: 34.7s remaining: 21.5s
630: learn: 0.2703133 total: 34.7s remaining: 21.4s
631: learn: 0.2702895 total: 34.8s remaining: 21.4s
632: learn: 0.2702067 total: 34.8s remaining: 21.3s
633: learn: 0.2701375 total: 34.9s remaining: 21.2s
634: learn: 0.2700947 total: 34.9s remaining: 21.2s
635: learn: 0.2699879 total: 35s remaining: 21.1s
636: learn: 0.2699564 total: 35s remaining: 21.1s
637: learn: 0.2698926 total: 35.1s remaining: 21s
638: learn: 0.2698371 total: 35.1s remaining: 21s
639: learn: 0.2697461 total: 35.2s remaining: 20.9s
640: learn: 0.2696929 total: 35.2s remaining: 20.8s
641: learn: 0.2696623 total: 35.3s remaining: 20.8s
642: learn: 0.2695759 total: 35.3s remaining: 20.7s
643: learn: 0.2694727 total: 35.4s remaining: 20.7s
644: learn: 0.2694178 total: 35.4s remaining: 20.6s
645: learn: 0.2692133 total: 35.5s remaining: 20.6s
646: learn: 0.2691143 total: 35.5s remaining: 20.5s
647: learn: 0.2690269 total: 35.6s remaining: 20.4s
648: learn: 0.2689324 total: 35.6s remaining: 20.4s
649: learn: 0.2688573 total: 35.7s remaining: 20.3s
650: learn: 0.2683936 total: 35.7s remaining: 20.3s
651: learn: 0.2683443 total: 35.8s remaining: 20.2s
652: learn: 0.2680010 total: 35.8s remaining: 20.1s
653: learn: 0.2679191 total: 35.9s remaining: 20.1s
654: learn: 0.2678659 total: 35.9s remaining: 20s
655: learn: 0.2678255 total: 36s remaining: 20s
656: learn: 0.2677032 total: 36s remaining: 19.9s
657: learn: 0.2676455 total: 36.1s remaining: 19.9s
658: learn: 0.2675462 total: 36.2s remaining: 19.8s
659: learn: 0.2674548 total: 36.2s remaining: 19.8s
660: learn: 0.2673128 total: 36.3s remaining: 19.7s
661: learn: 0.2672589 total: 36.3s remaining: 19.6s
662: learn: 0.2671985 total: 36.4s remaining: 19.6s
663: learn: 0.2671108 total: 36.4s remaining: 19.5s
664: learn: 0.2670797 total: 36.5s remaining: 19.5s
665: learn: 0.2670396 total: 36.5s remaining: 19.4s
666: learn: 0.2669870 total: 36.6s remaining: 19.3s
667: learn: 0.2668029 total: 36.6s remaining: 19.3s
668: learn: 0.2667099 total: 36.7s remaining: 19.2s
669: learn: 0.2666716 total: 36.7s remaining: 19.2s
670: learn: 0.2665178 total: 36.8s remaining: 19.1s
671: learn: 0.2664886 total: 36.8s remaining: 19.1s
672: learn: 0.2664478 total: 36.9s remaining: 19s
673: learn: 0.2664071 total: 36.9s remaining: 18.9s
674: learn: 0.2663887 total: 37s remaining: 18.9s
675: learn: 0.2663886 total: 37s remaining: 18.8s
676: learn: 0.2662919 total: 37.1s remaining: 18.8s
677: learn: 0.2662140 total: 37.1s remaining: 18.7s
678: learn: 0.2661186 total: 37.2s remaining: 18.7s
679: learn: 0.2660083 total: 37.2s remaining: 18.6s
680: learn: 0.2659285 total: 37.3s remaining: 18.6s
681: learn: 0.2657356 total: 37.4s remaining: 18.5s
682: learn: 0.2656143 total: 37.4s remaining: 18.5s
683: learn: 0.2655702 total: 37.5s remaining: 18.4s
684: learn: 0.2654410 total: 37.6s remaining: 18.4s
685: learn: 0.2652727 total: 37.6s remaining: 18.3s
686: learn: 0.2651316 total: 37.7s remaining: 18.3s
687: learn: 0.2651099 total: 37.7s remaining: 18.2s
688: learn: 0.2650617 total: 37.8s remaining: 18.2s
689: learn: 0.2650097 total: 37.9s remaining: 18.1s
690: learn: 0.2648973 total: 37.9s remaining: 18.1s
691: learn: 0.2647753 total: 38s remaining: 18s
692: learn: 0.2645993 total: 38s remaining: 17.9s
693: learn: 0.2645114 total: 38.1s remaining: 17.9s
694: learn: 0.2644575 total: 38.2s remaining: 17.8s
695: learn: 0.2643767 total: 38.2s remaining: 17.8s
696: learn: 0.2643766 total: 38.3s remaining: 17.7s
697: learn: 0.2643172 total: 38.3s remaining: 17.7s
698: learn: 0.2642570 total: 38.4s remaining: 17.6s
699: learn: 0.2640720 total: 38.4s remaining: 17.6s
700: learn: 0.2640020 total: 38.5s remaining: 17.5s
701: learn: 0.2639107 total: 38.6s remaining: 17.5s
702: learn: 0.2637503 total: 38.6s remaining: 17.4s
703: learn: 0.2636552 total: 38.7s remaining: 17.4s
704: learn: 0.2636060 total: 38.8s remaining: 17.3s
705: learn: 0.2634875 total: 38.8s remaining: 17.3s
706: learn: 0.2634295 total: 38.9s remaining: 17.2s
707: learn: 0.2633951 total: 39s remaining: 17.2s
708: learn: 0.2633525 total: 39s remaining: 17.1s
709: learn: 0.2632631 total: 39.1s remaining: 17.1s
710: learn: 0.2632630 total: 39.1s remaining: 17s
711: learn: 0.2631728 total: 39.2s remaining: 16.9s
712: learn: 0.2631686 total: 39.2s remaining: 16.9s
713: learn: 0.2631686 total: 39.3s remaining: 16.8s
714: learn: 0.2631139 total: 39.3s remaining: 16.8s
715: learn: 0.2631004 total: 39.4s remaining: 16.7s
716: learn: 0.2630568 total: 39.5s remaining: 16.7s
717: learn: 0.2630241 total: 39.5s remaining: 16.6s
718: learn: 0.2630236 total: 39.5s remaining: 16.6s
719: learn: 0.2628493 total: 39.6s remaining: 16.5s
720: learn: 0.2627348 total: 39.7s remaining: 16.4s
721: learn: 0.2625681 total: 39.7s remaining: 16.4s
722: learn: 0.2624825 total: 39.8s remaining: 16.3s
723: learn: 0.2624278 total: 39.8s remaining: 16.3s
724: learn: 0.2623412 total: 39.9s remaining: 16.2s
725: learn: 0.2622899 total: 40s remaining: 16.2s
726: learn: 0.2622318 total: 40s remaining: 16.1s
727: learn: 0.2621145 total: 40.1s remaining: 16.1s
728: learn: 0.2620547 total: 40.1s remaining: 16s
729: learn: 0.2620411 total: 40.2s remaining: 16s
730: learn: 0.2619706 total: 40.3s remaining: 15.9s
731: learn: 0.2618813 total: 40.3s remaining: 15.9s
732: learn: 0.2617529 total: 40.4s remaining: 15.8s
733: learn: 0.2617021 total: 40.4s remaining: 15.8s
734: learn: 0.2614789 total: 40.5s remaining: 15.7s
735: learn: 0.2614173 total: 40.5s remaining: 15.6s
736: learn: 0.2612320 total: 40.6s remaining: 15.6s
737: learn: 0.2610906 total: 40.6s remaining: 15.5s
738: learn: 0.2610262 total: 40.7s remaining: 15.5s
739: learn: 0.2609289 total: 40.7s remaining: 15.4s
740: learn: 0.2608993 total: 40.8s remaining: 15.4s
741: learn: 0.2608480 total: 40.8s remaining: 15.3s
742: learn: 0.2608106 total: 40.9s remaining: 15.2s
743: learn: 0.2607325 total: 40.9s remaining: 15.2s
744: learn: 0.2606384 total: 41s remaining: 15.1s
745: learn: 0.2606348 total: 41s remaining: 15.1s
746: learn: 0.2606334 total: 41.1s remaining: 15s
747: learn: 0.2605986 total: 41.1s remaining: 15s
748: learn: 0.2605605 total: 41.2s remaining: 14.9s
749: learn: 0.2604825 total: 41.2s remaining: 14.8s
750: learn: 0.2604354 total: 41.3s remaining: 14.8s
751: learn: 0.2602852 total: 41.3s remaining: 14.7s
752: learn: 0.2601861 total: 41.4s remaining: 14.7s
753: learn: 0.2601602 total: 41.5s remaining: 14.6s
754: learn: 0.2600867 total: 41.5s remaining: 14.6s
755: learn: 0.2600244 total: 41.6s remaining: 14.5s
756: learn: 0.2599201 total: 41.6s remaining: 14.5s
757: learn: 0.2599200 total: 41.6s remaining: 14.4s
758: learn: 0.2598569 total: 41.7s remaining: 14.3s
759: learn: 0.2597525 total: 41.7s remaining: 14.3s
760: learn: 0.2597070 total: 41.8s remaining: 14.2s
761: learn: 0.2596228 total: 41.8s remaining: 14.2s
762: learn: 0.2595991 total: 41.9s remaining: 14.1s
763: learn: 0.2595916 total: 41.9s remaining: 14.1s
764: learn: 0.2595426 total: 42s remaining: 14s
765: learn: 0.2594368 total: 42s remaining: 13.9s
766: learn: 0.2593813 total: 42.1s remaining: 13.9s
767: learn: 0.2593644 total: 42.1s remaining: 13.8s
768: learn: 0.2592708 total: 42.2s remaining: 13.8s
769: learn: 0.2591549 total: 42.2s remaining: 13.7s
770: learn: 0.2589749 total: 42.3s remaining: 13.7s
771: learn: 0.2588794 total: 42.3s remaining: 13.6s
772: learn: 0.2586602 total: 42.4s remaining: 13.5s
773: learn: 0.2586343 total: 42.4s remaining: 13.5s
774: learn: 0.2585744 total: 42.5s remaining: 13.4s
775: learn: 0.2585168 total: 42.6s remaining: 13.4s
776: learn: 0.2585157 total: 42.6s remaining: 13.3s
777: learn: 0.2584818 total: 42.6s remaining: 13.3s
778: learn: 0.2584444 total: 42.7s remaining: 13.2s
779: learn: 0.2583776 total: 42.7s remaining: 13.1s
780: learn: 0.2583258 total: 42.8s remaining: 13.1s
781: learn: 0.2582345 total: 42.8s remaining: 13s
782: learn: 0.2582102 total: 42.9s remaining: 13s
783: learn: 0.2581684 total: 42.9s remaining: 12.9s
784: learn: 0.2580530 total: 43s remaining: 12.9s
785: learn: 0.2579707 total: 43s remaining: 12.8s
786: learn: 0.2579069 total: 43.1s remaining: 12.8s
787: learn: 0.2577481 total: 43.1s remaining: 12.7s
788: learn: 0.2576602 total: 43.2s remaining: 12.6s
789: learn: 0.2575793 total: 43.2s remaining: 12.6s
790: learn: 0.2574490 total: 43.3s remaining: 12.5s
791: learn: 0.2573825 total: 43.3s remaining: 12.5s
792: learn: 0.2572917 total: 43.4s remaining: 12.4s
793: learn: 0.2572476 total: 43.4s remaining: 12.4s
794: learn: 0.2572143 total: 43.5s remaining: 12.3s
795: learn: 0.2571805 total: 43.5s remaining: 12.3s
796: learn: 0.2571205 total: 43.6s remaining: 12.2s
797: learn: 0.2570919 total: 43.6s remaining: 12.1s
798: learn: 0.2570179 total: 43.7s remaining: 12.1s
799: learn: 0.2569727 total: 43.7s remaining: 12s
800: learn: 0.2569114 total: 43.8s remaining: 12s
801: learn: 0.2568702 total: 43.9s remaining: 11.9s
802: learn: 0.2568060 total: 43.9s remaining: 11.9s
803: learn: 0.2568057 total: 44s remaining: 11.8s
804: learn: 0.2567276 total: 44s remaining: 11.8s
805: learn: 0.2567275 total: 44s remaining: 11.7s
806: learn: 0.2566273 total: 44.1s remaining: 11.6s
807: learn: 0.2566036 total: 44.2s remaining: 11.6s
808: learn: 0.2566033 total: 44.2s remaining: 11.5s
809: learn: 0.2564668 total: 44.3s remaining: 11.5s
810: learn: 0.2563972 total: 44.3s remaining: 11.4s
811: learn: 0.2563825 total: 44.4s remaining: 11.4s
812: learn: 0.2563391 total: 44.5s remaining: 11.3s
813: learn: 0.2563389 total: 44.5s remaining: 11.3s
814: learn: 0.2562691 total: 44.5s remaining: 11.2s
815: learn: 0.2562316 total: 44.6s remaining: 11.2s
816: learn: 0.2561040 total: 44.7s remaining: 11.1s
817: learn: 0.2560551 total: 44.7s remaining: 11s
818: learn: 0.2560550 total: 44.8s remaining: 11s
819: learn: 0.2558958 total: 44.8s remaining: 10.9s
820: learn: 0.2558319 total: 44.9s remaining: 10.9s
821: learn: 0.2557421 total: 44.9s remaining: 10.8s
822: learn: 0.2556910 total: 45s remaining: 10.8s
823: learn: 0.2556356 total: 45.1s remaining: 10.7s
824: learn: 0.2556070 total: 45.1s remaining: 10.7s
825: learn: 0.2555104 total: 45.2s remaining: 10.6s
826: learn: 0.2554886 total: 45.3s remaining: 10.6s
827: learn: 0.2554146 total: 45.3s remaining: 10.5s
828: learn: 0.2552900 total: 45.4s remaining: 10.5s
829: learn: 0.2551272 total: 45.4s remaining: 10.4s
830: learn: 0.2550693 total: 45.5s remaining: 10.3s
831: learn: 0.2549761 total: 45.6s remaining: 10.3s
832: learn: 0.2549754 total: 45.6s remaining: 10.2s
833: learn: 0.2549131 total: 45.6s remaining: 10.2s
834: learn: 0.2548160 total: 45.7s remaining: 10.1s
835: learn: 0.2547605 total: 45.8s remaining: 10.1s
836: learn: 0.2545440 total: 45.8s remaining: 10s
837: learn: 0.2544404 total: 45.9s remaining: 9.97s
838: learn: 0.2544399 total: 45.9s remaining: 9.9s
839: learn: 0.2544076 total: 46s remaining: 9.85s
840: learn: 0.2543456 total: 46s remaining: 9.8s
841: learn: 0.2543227 total: 46.1s remaining: 9.75s
842: learn: 0.2542584 total: 46.2s remaining: 9.69s
843: learn: 0.2542095 total: 46.2s remaining: 9.64s
844: learn: 0.2540650 total: 46.3s remaining: 9.59s
845: learn: 0.2539080 total: 46.3s remaining: 9.53s
846: learn: 0.2537291 total: 46.4s remaining: 9.48s
847: learn: 0.2536916 total: 46.5s remaining: 9.42s
848: learn: 0.2535733 total: 46.5s remaining: 9.37s
849: learn: 0.2535692 total: 46.6s remaining: 9.32s
850: learn: 0.2535236 total: 46.7s remaining: 9.26s
851: learn: 0.2534899 total: 46.7s remaining: 9.21s
852: learn: 0.2534152 total: 46.8s remaining: 9.16s
853: learn: 0.2533673 total: 46.8s remaining: 9.11s
854: learn: 0.2531264 total: 46.9s remaining: 9.05s
855: learn: 0.2530759 total: 47s remaining: 9s
856: learn: 0.2529155 total: 47s remaining: 8.95s
857: learn: 0.2528399 total: 47.1s remaining: 8.89s
858: learn: 0.2528063 total: 47.2s remaining: 8.84s
859: learn: 0.2527781 total: 47.2s remaining: 8.78s
860: learn: 0.2527688 total: 47.3s remaining: 8.73s
861: learn: 0.2527306 total: 47.3s remaining: 8.67s
862: learn: 0.2526517 total: 47.4s remaining: 8.62s
863: learn: 0.2526026 total: 47.4s remaining: 8.56s
864: learn: 0.2526017 total: 47.4s remaining: 8.5s
865: learn: 0.2525791 total: 47.5s remaining: 8.44s
866: learn: 0.2525106 total: 47.5s remaining: 8.39s
867: learn: 0.2525065 total: 47.6s remaining: 8.33s
868: learn: 0.2524710 total: 47.6s remaining: 8.28s
869: learn: 0.2524234 total: 47.7s remaining: 8.22s
870: learn: 0.2523331 total: 47.8s remaining: 8.17s
871: learn: 0.2522761 total: 47.8s remaining: 8.11s
872: learn: 0.2522559 total: 47.9s remaining: 8.06s
873: learn: 0.2521721 total: 47.9s remaining: 8s
874: learn: 0.2520185 total: 48s remaining: 7.95s
875: learn: 0.2520184 total: 48s remaining: 7.89s
876: learn: 0.2520184 total: 48s remaining: 7.83s
877: learn: 0.2519806 total: 48.1s remaining: 7.77s
878: learn: 0.2519747 total: 48.1s remaining: 7.72s
879: learn: 0.2519054 total: 48.2s remaining: 7.66s
880: learn: 0.2519023 total: 48.2s remaining: 7.6s
881: learn: 0.2518307 total: 48.3s remaining: 7.55s
882: learn: 0.2517479 total: 48.3s remaining: 7.5s
883: learn: 0.2516764 total: 48.4s remaining: 7.44s
884: learn: 0.2516649 total: 48.4s remaining: 7.39s
885: learn: 0.2516146 total: 48.5s remaining: 7.33s
886: learn: 0.2515755 total: 48.5s remaining: 7.28s
887: learn: 0.2515755 total: 48.5s remaining: 7.22s
888: learn: 0.2515088 total: 48.6s remaining: 7.16s
889: learn: 0.2515072 total: 48.6s remaining: 7.1s
890: learn: 0.2514675 total: 48.7s remaining: 7.05s
891: learn: 0.2512975 total: 48.7s remaining: 6.99s
892: learn: 0.2512459 total: 48.8s remaining: 6.94s
893: learn: 0.2511839 total: 48.9s remaining: 6.89s
894: learn: 0.2511476 total: 48.9s remaining: 6.83s
895: learn: 0.2510779 total: 49s remaining: 6.78s
896: learn: 0.2510597 total: 49s remaining: 6.72s
897: learn: 0.2509589 total: 49.1s remaining: 6.67s
898: learn: 0.2508576 total: 49.1s remaining: 6.62s
899: learn: 0.2508241 total: 49.2s remaining: 6.56s
900: learn: 0.2508004 total: 49.3s remaining: 6.5s
901: learn: 0.2506571 total: 49.3s remaining: 6.45s
902: learn: 0.2506472 total: 49.4s remaining: 6.39s
903: learn: 0.2505735 total: 49.4s remaining: 6.34s
904: learn: 0.2505546 total: 49.5s remaining: 6.29s
905: learn: 0.2505176 total: 49.5s remaining: 6.23s
906: learn: 0.2503970 total: 49.6s remaining: 6.18s
907: learn: 0.2503514 total: 49.6s remaining: 6.12s
908: learn: 0.2501431 total: 49.7s remaining: 6.07s
909: learn: 0.2499881 total: 49.7s remaining: 6.01s
910: learn: 0.2499389 total: 49.8s remaining: 5.96s
911: learn: 0.2499085 total: 49.9s remaining: 5.9s
912: learn: 0.2498881 total: 49.9s remaining: 5.85s
913: learn: 0.2497615 total: 50s remaining: 5.8s
914: learn: 0.2497574 total: 50s remaining: 5.74s
915: learn: 0.2495564 total: 50.1s remaining: 5.69s
916: learn: 0.2495011 total: 50.1s remaining: 5.63s
917: learn: 0.2494451 total: 50.2s remaining: 5.58s
918: learn: 0.2493738 total: 50.2s remaining: 5.52s
919: learn: 0.2493084 total: 50.3s remaining: 5.47s
920: learn: 0.2493031 total: 50.4s remaining: 5.41s
921: learn: 0.2492803 total: 50.4s remaining: 5.36s
922: learn: 0.2492802 total: 50.4s remaining: 5.3s
923: learn: 0.2492333 total: 50.5s remaining: 5.25s
924: learn: 0.2492277 total: 50.5s remaining: 5.19s
925: learn: 0.2491488 total: 50.6s remaining: 5.13s
926: learn: 0.2491121 total: 50.7s remaining: 5.08s
927: learn: 0.2491088 total: 50.7s remaining: 5.03s
928: learn: 0.2491048 total: 50.8s remaining: 4.97s
929: learn: 0.2490581 total: 50.9s remaining: 4.92s
930: learn: 0.2490146 total: 50.9s remaining: 4.87s
931: learn: 0.2488984 total: 51s remaining: 4.82s
932: learn: 0.2488130 total: 51.1s remaining: 4.76s
933: learn: 0.2488052 total: 51.1s remaining: 4.71s
934: learn: 0.2487929 total: 51.2s remaining: 4.66s
935: learn: 0.2487016 total: 51.3s remaining: 4.6s
936: learn: 0.2486500 total: 51.3s remaining: 4.55s
937: learn: 0.2486500 total: 51.4s remaining: 4.49s
938: learn: 0.2486335 total: 51.4s remaining: 4.44s
939: learn: 0.2486334 total: 51.5s remaining: 4.38s
940: learn: 0.2485295 total: 51.5s remaining: 4.33s
941: learn: 0.2485145 total: 51.6s remaining: 4.27s
942: learn: 0.2484534 total: 51.7s remaining: 4.22s
943: learn: 0.2483413 total: 51.7s remaining: 4.17s
944: learn: 0.2483091 total: 51.8s remaining: 4.11s
945: learn: 0.2481685 total: 51.9s remaining: 4.06s
946: learn: 0.2481685 total: 51.9s remaining: 4s
947: learn: 0.2480299 total: 52s remaining: 3.95s
948: learn: 0.2479347 total: 52.1s remaining: 3.9s
949: learn: 0.2479032 total: 52.2s remaining: 3.84s
950: learn: 0.2479032 total: 52.2s remaining: 3.79s
951: learn: 0.2477957 total: 52.3s remaining: 3.73s
952: learn: 0.2477668 total: 52.3s remaining: 3.68s
953: learn: 0.2477640 total: 52.4s remaining: 3.62s
954: learn: 0.2477497 total: 52.4s remaining: 3.57s
955: learn: 0.2476907 total: 52.5s remaining: 3.52s
956: learn: 0.2476215 total: 52.6s remaining: 3.46s
957: learn: 0.2476215 total: 52.6s remaining: 3.4s
958: learn: 0.2475405 total: 52.7s remaining: 3.35s
959: learn: 0.2475107 total: 52.8s remaining: 3.3s
960: learn: 0.2474598 total: 52.8s remaining: 3.24s
961: learn: 0.2474078 total: 52.9s remaining: 3.19s
962: learn: 0.2473717 total: 53s remaining: 3.13s
963: learn: 0.2473705 total: 53s remaining: 3.08s
964: learn: 0.2473203 total: 53.1s remaining: 3.02s
965: learn: 0.2472680 total: 53.1s remaining: 2.97s
966: learn: 0.2472199 total: 53.2s remaining: 2.92s
967: learn: 0.2471761 total: 53.3s remaining: 2.86s
968: learn: 0.2471642 total: 53.3s remaining: 2.81s
969: learn: 0.2471277 total: 53.4s remaining: 2.75s
970: learn: 0.2471277 total: 53.4s remaining: 2.7s
971: learn: 0.2471118 total: 53.5s remaining: 2.64s
972: learn: 0.2471002 total: 53.6s remaining: 2.59s
973: learn: 0.2470841 total: 53.6s remaining: 2.53s
974: learn: 0.2470346 total: 53.7s remaining: 2.48s
975: learn: 0.2470345 total: 53.7s remaining: 2.42s
976: learn: 0.2469759 total: 53.8s remaining: 2.37s
977: learn: 0.2469759 total: 53.9s remaining: 2.31s
978: learn: 0.2469264 total: 53.9s remaining: 2.26s
979: learn: 0.2468869 total: 54s remaining: 2.2s
980: learn: 0.2468676 total: 54.1s remaining: 2.15s
981: learn: 0.2467108 total: 54.1s remaining: 2.09s
982: learn: 0.2466369 total: 54.2s remaining: 2.04s
983: learn: 0.2465730 total: 54.2s remaining: 1.98s
984: learn: 0.2464943 total: 54.3s remaining: 1.93s
985: learn: 0.2464720 total: 54.3s remaining: 1.87s
986: learn: 0.2464507 total: 54.4s remaining: 1.82s
987: learn: 0.2464485 total: 54.4s remaining: 1.76s
988: learn: 0.2463844 total: 54.5s remaining: 1.71s
989: learn: 0.2463844 total: 54.5s remaining: 1.65s
990: learn: 0.2463843 total: 54.5s remaining: 1.59s
991: learn: 0.2463842 total: 54.5s remaining: 1.54s
992: learn: 0.2463745 total: 54.6s remaining: 1.48s
993: learn: 0.2463523 total: 54.6s remaining: 1.43s
994: learn: 0.2463432 total: 54.7s remaining: 1.37s
995: learn: 0.2463274 total: 54.7s remaining: 1.32s
996: learn: 0.2463274 total: 54.7s remaining: 1.26s
997: learn: 0.2462695 total: 54.8s remaining: 1.21s
998: learn: 0.2461776 total: 54.9s remaining: 1.15s
999: learn: 0.2461203 total: 54.9s remaining: 1.1s
1000: learn: 0.2459458 total: 55s remaining: 1.04s
1001: learn: 0.2458883 total: 55s remaining: 988ms
1002: learn: 0.2458653 total: 55.1s remaining: 933ms
1003: learn: 0.2458187 total: 55.1s remaining: 878ms
1004: learn: 0.2458187 total: 55.1s remaining: 823ms
1005: learn: 0.2457870 total: 55.2s remaining: 768ms
1006: learn: 0.2457260 total: 55.3s remaining: 713ms
1007: learn: 0.2456957 total: 55.3s remaining: 659ms
1008: learn: 0.2456534 total: 55.4s remaining: 604ms
1009: learn: 0.2456386 total: 55.4s remaining: 549ms
1010: learn: 0.2455334 total: 55.5s remaining: 494ms
1011: learn: 0.2454118 total: 55.5s remaining: 439ms
1012: learn: 0.2453593 total: 55.6s remaining: 384ms
1013: learn: 0.2453188 total: 55.6s remaining: 329ms
1014: learn: 0.2452880 total: 55.7s remaining: 274ms
1015: learn: 0.2452880 total: 55.7s remaining: 219ms
1016: learn: 0.2452607 total: 55.8s remaining: 164ms
1017: learn: 0.2452562 total: 55.8s remaining: 110ms
1018: learn: 0.2452562 total: 55.8s remaining: 54.8ms
1019: learn: 0.2452202 total: 55.9s remaining: 0us
Finished training fold 2 - running score 0.8618983608107144
Running fold 3, 15737 train samples, 2622 validation samples
0: learn: 0.6479581 total: 54.1ms remaining: 55.1s
1: learn: 0.6088767 total: 108ms remaining: 54.8s
2: learn: 0.5754856 total: 161ms remaining: 54.5s
3: learn: 0.5467985 total: 214ms remaining: 54.4s
4: learn: 0.5217744 total: 269ms remaining: 54.5s
5: learn: 0.5002940 total: 321ms remaining: 54.2s
6: learn: 0.4819237 total: 371ms remaining: 53.6s
7: learn: 0.4659351 total: 421ms remaining: 53.3s
8: learn: 0.4524082 total: 483ms remaining: 54.3s
9: learn: 0.4405077 total: 535ms remaining: 54.1s
10: learn: 0.4303901 total: 586ms remaining: 53.8s
11: learn: 0.4215387 total: 638ms remaining: 53.6s
12: learn: 0.4138120 total: 688ms remaining: 53.3s
13: learn: 0.4070878 total: 737ms remaining: 53s
14: learn: 0.4014786 total: 793ms remaining: 53.1s
15: learn: 0.3965126 total: 849ms remaining: 53.3s
16: learn: 0.3921758 total: 907ms remaining: 53.5s
17: learn: 0.3883752 total: 962ms remaining: 53.5s
18: learn: 0.3849404 total: 1.02s remaining: 53.6s
19: learn: 0.3820913 total: 1.07s remaining: 53.7s
20: learn: 0.3795515 total: 1.13s remaining: 53.8s
21: learn: 0.3773674 total: 1.19s remaining: 53.9s
22: learn: 0.3753156 total: 1.25s remaining: 54s
23: learn: 0.3735621 total: 1.31s remaining: 54.5s
24: learn: 0.3721059 total: 1.37s remaining: 54.6s
25: learn: 0.3706652 total: 1.42s remaining: 54.5s
26: learn: 0.3694310 total: 1.47s remaining: 54.2s
27: learn: 0.3682859 total: 1.53s remaining: 54.1s
28: learn: 0.3673150 total: 1.58s remaining: 53.9s
29: learn: 0.3664591 total: 1.63s remaining: 53.8s
30: learn: 0.3655636 total: 1.68s remaining: 53.6s
31: learn: 0.3649043 total: 1.73s remaining: 53.5s
32: learn: 0.3642651 total: 1.78s remaining: 53.3s
33: learn: 0.3636884 total: 1.83s remaining: 53.1s
34: learn: 0.3631720 total: 1.88s remaining: 53s
35: learn: 0.3627135 total: 1.94s remaining: 52.9s
36: learn: 0.3622344 total: 1.99s remaining: 52.8s
37: learn: 0.3616877 total: 2.05s remaining: 52.9s
38: learn: 0.3613655 total: 2.11s remaining: 53s
39: learn: 0.3609521 total: 2.16s remaining: 52.9s
40: learn: 0.3605880 total: 2.21s remaining: 52.8s
41: learn: 0.3602878 total: 2.26s remaining: 52.7s
42: learn: 0.3599233 total: 2.31s remaining: 52.6s
43: learn: 0.3596283 total: 2.37s remaining: 52.5s
44: learn: 0.3592207 total: 2.42s remaining: 52.4s
45: learn: 0.3589106 total: 2.47s remaining: 52.3s
46: learn: 0.3585692 total: 2.52s remaining: 52.2s
47: learn: 0.3582986 total: 2.57s remaining: 52.1s
48: learn: 0.3579262 total: 2.63s remaining: 52.2s
49: learn: 0.3577104 total: 2.7s remaining: 52.4s
50: learn: 0.3574516 total: 2.77s remaining: 52.6s
51: learn: 0.3570536 total: 2.83s remaining: 52.8s
52: learn: 0.3566843 total: 2.91s remaining: 53s
53: learn: 0.3564295 total: 2.97s remaining: 53.1s
54: learn: 0.3563187 total: 3.03s remaining: 53.2s
55: learn: 0.3560284 total: 3.1s remaining: 53.4s
56: learn: 0.3558788 total: 3.18s remaining: 53.7s
57: learn: 0.3557353 total: 3.24s remaining: 53.8s
58: learn: 0.3555438 total: 3.3s remaining: 53.8s
59: learn: 0.3552768 total: 3.38s remaining: 54s
60: learn: 0.3551517 total: 3.46s remaining: 54.3s
61: learn: 0.3549624 total: 3.53s remaining: 54.5s
62: learn: 0.3548764 total: 3.59s remaining: 54.6s
63: learn: 0.3546886 total: 3.67s remaining: 54.8s
64: learn: 0.3543250 total: 3.74s remaining: 55s
65: learn: 0.3541304 total: 3.82s remaining: 55.2s
66: learn: 0.3539863 total: 3.89s remaining: 55.4s
67: learn: 0.3536844 total: 3.96s remaining: 55.5s
68: learn: 0.3535695 total: 4.05s remaining: 55.8s
69: learn: 0.3534054 total: 4.12s remaining: 55.9s
70: learn: 0.3532476 total: 4.19s remaining: 56s
71: learn: 0.3528641 total: 4.25s remaining: 56s
72: learn: 0.3526252 total: 4.31s remaining: 56s
73: learn: 0.3523938 total: 4.38s remaining: 55.9s
74: learn: 0.3522617 total: 4.44s remaining: 56s
75: learn: 0.3519713 total: 4.52s remaining: 56.2s
76: learn: 0.3518164 total: 4.59s remaining: 56.3s
77: learn: 0.3515649 total: 4.67s remaining: 56.4s
78: learn: 0.3513454 total: 4.73s remaining: 56.4s
79: learn: 0.3511569 total: 4.79s remaining: 56.3s
80: learn: 0.3510624 total: 4.85s remaining: 56.3s
81: learn: 0.3508581 total: 4.92s remaining: 56.2s
82: learn: 0.3506381 total: 4.98s remaining: 56.2s
83: learn: 0.3502583 total: 5.04s remaining: 56.2s
84: learn: 0.3501404 total: 5.11s remaining: 56.2s
85: learn: 0.3499285 total: 5.17s remaining: 56.1s
86: learn: 0.3495793 total: 5.23s remaining: 56.1s
87: learn: 0.3494391 total: 5.29s remaining: 56.1s
88: learn: 0.3492248 total: 5.36s remaining: 56s
89: learn: 0.3489453 total: 5.42s remaining: 56s
90: learn: 0.3486874 total: 5.48s remaining: 55.9s
91: learn: 0.3484192 total: 5.54s remaining: 55.9s
92: learn: 0.3483002 total: 5.61s remaining: 55.9s
93: learn: 0.3481681 total: 5.67s remaining: 55.9s
94: learn: 0.3479659 total: 5.73s remaining: 55.8s
95: learn: 0.3476465 total: 5.8s remaining: 55.8s
96: learn: 0.3474931 total: 5.86s remaining: 55.8s
97: learn: 0.3472480 total: 5.93s remaining: 55.8s
98: learn: 0.3470347 total: 5.99s remaining: 55.7s
99: learn: 0.3468979 total: 6.05s remaining: 55.6s
100: learn: 0.3467172 total: 6.1s remaining: 55.5s
101: learn: 0.3465056 total: 6.15s remaining: 55.4s
102: learn: 0.3463113 total: 6.2s remaining: 55.2s
103: learn: 0.3459968 total: 6.25s remaining: 55.1s
104: learn: 0.3457688 total: 6.3s remaining: 54.9s
105: learn: 0.3456076 total: 6.35s remaining: 54.7s
106: learn: 0.3452315 total: 6.4s remaining: 54.6s
107: learn: 0.3448946 total: 6.45s remaining: 54.5s
108: learn: 0.3447600 total: 6.5s remaining: 54.3s
109: learn: 0.3447071 total: 6.55s remaining: 54.2s
110: learn: 0.3445849 total: 6.6s remaining: 54.1s
111: learn: 0.3441840 total: 6.66s remaining: 54s
112: learn: 0.3439002 total: 6.71s remaining: 53.9s
113: learn: 0.3437168 total: 6.76s remaining: 53.7s
114: learn: 0.3435539 total: 6.81s remaining: 53.6s
115: learn: 0.3433793 total: 6.86s remaining: 53.5s
116: learn: 0.3432827 total: 6.91s remaining: 53.4s
117: learn: 0.3431261 total: 6.96s remaining: 53.2s
118: learn: 0.3429061 total: 7.02s remaining: 53.1s
119: learn: 0.3425668 total: 7.07s remaining: 53s
120: learn: 0.3423282 total: 7.12s remaining: 52.9s
121: learn: 0.3421069 total: 7.17s remaining: 52.8s
122: learn: 0.3417590 total: 7.22s remaining: 52.6s
123: learn: 0.3415691 total: 7.27s remaining: 52.5s
124: learn: 0.3412517 total: 7.32s remaining: 52.4s
125: learn: 0.3410968 total: 7.37s remaining: 52.3s
126: learn: 0.3408442 total: 7.42s remaining: 52.2s
127: learn: 0.3407545 total: 7.47s remaining: 52.1s
128: learn: 0.3405341 total: 7.52s remaining: 51.9s
129: learn: 0.3403128 total: 7.57s remaining: 51.8s
130: learn: 0.3401885 total: 7.62s remaining: 51.7s
131: learn: 0.3401148 total: 7.67s remaining: 51.6s
132: learn: 0.3399784 total: 7.72s remaining: 51.5s
133: learn: 0.3398441 total: 7.77s remaining: 51.4s
134: learn: 0.3397258 total: 7.82s remaining: 51.3s
135: learn: 0.3395818 total: 7.87s remaining: 51.2s
136: learn: 0.3393893 total: 7.92s remaining: 51s
137: learn: 0.3393097 total: 7.97s remaining: 50.9s
138: learn: 0.3391212 total: 8.02s remaining: 50.8s
139: learn: 0.3389349 total: 8.07s remaining: 50.7s
140: learn: 0.3387520 total: 8.12s remaining: 50.6s
141: learn: 0.3386163 total: 8.17s remaining: 50.5s
142: learn: 0.3383953 total: 8.22s remaining: 50.4s
143: learn: 0.3382649 total: 8.27s remaining: 50.3s
144: learn: 0.3380191 total: 8.31s remaining: 50.2s
145: learn: 0.3378270 total: 8.36s remaining: 50.1s
146: learn: 0.3376933 total: 8.41s remaining: 50s
147: learn: 0.3374459 total: 8.46s remaining: 49.9s
148: learn: 0.3373202 total: 8.51s remaining: 49.7s
149: learn: 0.3372007 total: 8.56s remaining: 49.6s
150: learn: 0.3370025 total: 8.61s remaining: 49.5s
151: learn: 0.3367953 total: 8.66s remaining: 49.4s
152: learn: 0.3367132 total: 8.71s remaining: 49.3s
153: learn: 0.3365929 total: 8.76s remaining: 49.3s
154: learn: 0.3363706 total: 8.81s remaining: 49.2s
155: learn: 0.3360444 total: 8.86s remaining: 49.1s
156: learn: 0.3358519 total: 8.91s remaining: 49s
157: learn: 0.3355437 total: 8.96s remaining: 48.9s
158: learn: 0.3353508 total: 9.01s remaining: 48.8s
159: learn: 0.3352039 total: 9.06s remaining: 48.7s
160: learn: 0.3350340 total: 9.11s remaining: 48.6s
161: learn: 0.3347060 total: 9.16s remaining: 48.5s
162: learn: 0.3345689 total: 9.21s remaining: 48.4s
163: learn: 0.3344198 total: 9.26s remaining: 48.3s
164: learn: 0.3342320 total: 9.31s remaining: 48.3s
165: learn: 0.3340242 total: 9.37s remaining: 48.2s
166: learn: 0.3338869 total: 9.42s remaining: 48.1s
167: learn: 0.3336902 total: 9.47s remaining: 48s
168: learn: 0.3335063 total: 9.53s remaining: 48s
169: learn: 0.3332890 total: 9.59s remaining: 48s
170: learn: 0.3330531 total: 9.65s remaining: 47.9s
171: learn: 0.3327127 total: 9.72s remaining: 47.9s
172: learn: 0.3325127 total: 9.78s remaining: 47.9s
173: learn: 0.3321644 total: 9.85s remaining: 47.9s
174: learn: 0.3318907 total: 9.91s remaining: 47.9s
175: learn: 0.3317622 total: 9.97s remaining: 47.8s
176: learn: 0.3316046 total: 10s remaining: 47.8s
177: learn: 0.3313377 total: 10.1s remaining: 47.7s
178: learn: 0.3311823 total: 10.2s remaining: 47.7s
179: learn: 0.3310088 total: 10.2s remaining: 47.7s
180: learn: 0.3309027 total: 10.3s remaining: 47.6s
181: learn: 0.3307326 total: 10.3s remaining: 47.6s
182: learn: 0.3306332 total: 10.4s remaining: 47.6s
183: learn: 0.3304030 total: 10.5s remaining: 47.5s
184: learn: 0.3301445 total: 10.5s remaining: 47.5s
185: learn: 0.3298925 total: 10.6s remaining: 47.5s
186: learn: 0.3297069 total: 10.7s remaining: 47.4s
187: learn: 0.3294684 total: 10.7s remaining: 47.4s
188: learn: 0.3292685 total: 10.8s remaining: 47.4s
189: learn: 0.3290939 total: 10.8s remaining: 47.3s
190: learn: 0.3288476 total: 10.9s remaining: 47.3s
191: learn: 0.3286520 total: 11s remaining: 47.3s
192: learn: 0.3284058 total: 11s remaining: 47.3s
193: learn: 0.3281778 total: 11.1s remaining: 47.2s
194: learn: 0.3280319 total: 11.2s remaining: 47.2s
195: learn: 0.3277599 total: 11.2s remaining: 47.2s
196: learn: 0.3274643 total: 11.3s remaining: 47.1s
197: learn: 0.3272759 total: 11.3s remaining: 47.1s
198: learn: 0.3271313 total: 11.4s remaining: 47.1s
199: learn: 0.3269030 total: 11.5s remaining: 47s
200: learn: 0.3265870 total: 11.5s remaining: 47s
201: learn: 0.3264443 total: 11.6s remaining: 46.9s
202: learn: 0.3263133 total: 11.7s remaining: 46.9s
203: learn: 0.3261196 total: 11.7s remaining: 46.9s
204: learn: 0.3259071 total: 11.8s remaining: 46.8s
205: learn: 0.3256304 total: 11.8s remaining: 46.8s
206: learn: 0.3255249 total: 11.9s remaining: 46.7s
207: learn: 0.3253362 total: 12s remaining: 46.7s
208: learn: 0.3250879 total: 12s remaining: 46.7s
209: learn: 0.3248517 total: 12.1s remaining: 46.7s
210: learn: 0.3245673 total: 12.2s remaining: 46.6s
211: learn: 0.3242886 total: 12.2s remaining: 46.6s
212: learn: 0.3241195 total: 12.3s remaining: 46.6s
213: learn: 0.3239850 total: 12.3s remaining: 46.5s
214: learn: 0.3237541 total: 12.4s remaining: 46.5s
215: learn: 0.3237532 total: 12.4s remaining: 46.3s
216: learn: 0.3235145 total: 12.5s remaining: 46.3s
217: learn: 0.3234128 total: 12.6s remaining: 46.2s
218: learn: 0.3232370 total: 12.6s remaining: 46.2s
219: learn: 0.3229215 total: 12.7s remaining: 46.2s
220: learn: 0.3226724 total: 12.8s remaining: 46.1s
221: learn: 0.3224093 total: 12.8s remaining: 46.1s
222: learn: 0.3222292 total: 12.9s remaining: 46s
223: learn: 0.3220994 total: 12.9s remaining: 45.9s
224: learn: 0.3218025 total: 13s remaining: 45.8s
225: learn: 0.3215183 total: 13s remaining: 45.8s
226: learn: 0.3212395 total: 13.1s remaining: 45.7s
227: learn: 0.3210956 total: 13.1s remaining: 45.6s
228: learn: 0.3208310 total: 13.2s remaining: 45.5s
229: learn: 0.3206963 total: 13.2s remaining: 45.5s
230: learn: 0.3205149 total: 13.3s remaining: 45.4s
231: learn: 0.3204162 total: 13.3s remaining: 45.3s
232: learn: 0.3201710 total: 13.4s remaining: 45.2s
233: learn: 0.3200560 total: 13.4s remaining: 45.1s
234: learn: 0.3198263 total: 13.5s remaining: 45.1s
235: learn: 0.3197179 total: 13.5s remaining: 45s
236: learn: 0.3195308 total: 13.6s remaining: 44.9s
237: learn: 0.3194705 total: 13.6s remaining: 44.8s
238: learn: 0.3192716 total: 13.7s remaining: 44.7s
239: learn: 0.3191656 total: 13.7s remaining: 44.6s
240: learn: 0.3190164 total: 13.8s remaining: 44.6s
241: learn: 0.3188705 total: 13.8s remaining: 44.5s
242: learn: 0.3186977 total: 13.9s remaining: 44.4s
243: learn: 0.3185953 total: 13.9s remaining: 44.3s
244: learn: 0.3184181 total: 14s remaining: 44.2s
245: learn: 0.3181426 total: 14s remaining: 44.2s
246: learn: 0.3177572 total: 14.1s remaining: 44.1s
247: learn: 0.3176050 total: 14.1s remaining: 44s
248: learn: 0.3174590 total: 14.2s remaining: 43.9s
249: learn: 0.3173510 total: 14.2s remaining: 43.8s
250: learn: 0.3172424 total: 14.3s remaining: 43.8s
251: learn: 0.3170935 total: 14.3s remaining: 43.7s
252: learn: 0.3167888 total: 14.4s remaining: 43.6s
253: learn: 0.3164680 total: 14.4s remaining: 43.6s
254: learn: 0.3162816 total: 14.5s remaining: 43.5s
255: learn: 0.3161754 total: 14.5s remaining: 43.4s
256: learn: 0.3161221 total: 14.6s remaining: 43.3s
257: learn: 0.3159030 total: 14.6s remaining: 43.3s
258: learn: 0.3157119 total: 14.7s remaining: 43.2s
259: learn: 0.3153421 total: 14.8s remaining: 43.1s
260: learn: 0.3152389 total: 14.8s remaining: 43s
261: learn: 0.3151272 total: 14.9s remaining: 43s
262: learn: 0.3149569 total: 14.9s remaining: 42.9s
263: learn: 0.3146496 total: 15s remaining: 42.8s
264: learn: 0.3144967 total: 15s remaining: 42.8s
265: learn: 0.3143953 total: 15.1s remaining: 42.7s
266: learn: 0.3142650 total: 15.1s remaining: 42.6s
267: learn: 0.3140704 total: 15.2s remaining: 42.6s
268: learn: 0.3139341 total: 15.2s remaining: 42.5s
269: learn: 0.3137153 total: 15.3s remaining: 42.4s
270: learn: 0.3136195 total: 15.3s remaining: 42.4s
271: learn: 0.3132942 total: 15.4s remaining: 42.3s
272: learn: 0.3130729 total: 15.4s remaining: 42.2s
273: learn: 0.3127889 total: 15.5s remaining: 42.2s
274: learn: 0.3123887 total: 15.5s remaining: 42.1s
275: learn: 0.3122683 total: 15.6s remaining: 42s
276: learn: 0.3121708 total: 15.7s remaining: 42s
277: learn: 0.3120485 total: 15.7s remaining: 41.9s
278: learn: 0.3118692 total: 15.7s remaining: 41.8s
279: learn: 0.3117601 total: 15.8s remaining: 41.7s
280: learn: 0.3116280 total: 15.8s remaining: 41.7s
281: learn: 0.3114421 total: 15.9s remaining: 41.6s
282: learn: 0.3112355 total: 15.9s remaining: 41.5s
283: learn: 0.3110946 total: 16s remaining: 41.4s
284: learn: 0.3109252 total: 16s remaining: 41.4s
285: learn: 0.3107455 total: 16.1s remaining: 41.3s
286: learn: 0.3105983 total: 16.1s remaining: 41.2s
287: learn: 0.3104840 total: 16.2s remaining: 41.2s
288: learn: 0.3103893 total: 16.2s remaining: 41.1s
289: learn: 0.3100791 total: 16.3s remaining: 41.1s
290: learn: 0.3099120 total: 16.4s remaining: 41s
291: learn: 0.3097026 total: 16.5s remaining: 41s
292: learn: 0.3096262 total: 16.5s remaining: 41s
293: learn: 0.3095402 total: 16.6s remaining: 40.9s
294: learn: 0.3093566 total: 16.6s remaining: 40.9s
295: learn: 0.3091493 total: 16.7s remaining: 40.8s
296: learn: 0.3088562 total: 16.8s remaining: 40.8s
297: learn: 0.3087662 total: 16.8s remaining: 40.7s
298: learn: 0.3086323 total: 16.9s remaining: 40.7s
299: learn: 0.3085499 total: 16.9s remaining: 40.6s
300: learn: 0.3084561 total: 17s remaining: 40.6s
301: learn: 0.3081527 total: 17.1s remaining: 40.6s
302: learn: 0.3079996 total: 17.1s remaining: 40.5s
303: learn: 0.3077535 total: 17.2s remaining: 40.5s
304: learn: 0.3075106 total: 17.2s remaining: 40.4s
305: learn: 0.3072510 total: 17.3s remaining: 40.4s
306: learn: 0.3071274 total: 17.4s remaining: 40.3s
307: learn: 0.3068391 total: 17.4s remaining: 40.3s
308: learn: 0.3067590 total: 17.5s remaining: 40.3s
309: learn: 0.3065628 total: 17.6s remaining: 40.2s
310: learn: 0.3064766 total: 17.6s remaining: 40.2s
311: learn: 0.3063051 total: 17.7s remaining: 40.1s
312: learn: 0.3060450 total: 17.7s remaining: 40.1s
313: learn: 0.3058452 total: 17.8s remaining: 40s
314: learn: 0.3057452 total: 17.9s remaining: 40s
315: learn: 0.3055237 total: 17.9s remaining: 39.9s
316: learn: 0.3054269 total: 18s remaining: 39.9s
317: learn: 0.3052447 total: 18s remaining: 39.8s
318: learn: 0.3050632 total: 18.1s remaining: 39.8s
319: learn: 0.3048837 total: 18.2s remaining: 39.7s
320: learn: 0.3047926 total: 18.2s remaining: 39.7s
321: learn: 0.3045993 total: 18.3s remaining: 39.6s
322: learn: 0.3045684 total: 18.4s remaining: 39.6s
323: learn: 0.3044848 total: 18.4s remaining: 39.6s
324: learn: 0.3043900 total: 18.5s remaining: 39.5s
325: learn: 0.3043373 total: 18.5s remaining: 39.5s
326: learn: 0.3042262 total: 18.6s remaining: 39.4s
327: learn: 0.3040673 total: 18.7s remaining: 39.4s
328: learn: 0.3038944 total: 18.7s remaining: 39.3s
329: learn: 0.3037058 total: 18.8s remaining: 39.3s
330: learn: 0.3035773 total: 18.9s remaining: 39.2s
331: learn: 0.3034622 total: 18.9s remaining: 39.2s
332: learn: 0.3033190 total: 19s remaining: 39.1s
333: learn: 0.3032135 total: 19s remaining: 39.1s
334: learn: 0.3030612 total: 19.1s remaining: 39s
335: learn: 0.3028753 total: 19.2s remaining: 39s
336: learn: 0.3027239 total: 19.2s remaining: 38.9s
337: learn: 0.3025832 total: 19.3s remaining: 38.9s
338: learn: 0.3024633 total: 19.3s remaining: 38.8s
339: learn: 0.3024255 total: 19.4s remaining: 38.8s
340: learn: 0.3023239 total: 19.5s remaining: 38.8s
341: learn: 0.3022538 total: 19.5s remaining: 38.7s
342: learn: 0.3020846 total: 19.6s remaining: 38.7s
343: learn: 0.3020053 total: 19.7s remaining: 38.6s
344: learn: 0.3017909 total: 19.7s remaining: 38.6s
345: learn: 0.3016833 total: 19.8s remaining: 38.5s
346: learn: 0.3016198 total: 19.8s remaining: 38.4s
347: learn: 0.3014579 total: 19.9s remaining: 38.4s
348: learn: 0.3012201 total: 19.9s remaining: 38.3s
349: learn: 0.3011527 total: 20s remaining: 38.2s
350: learn: 0.3010232 total: 20s remaining: 38.2s
351: learn: 0.3009174 total: 20.1s remaining: 38.1s
352: learn: 0.3006850 total: 20.1s remaining: 38s
353: learn: 0.3005051 total: 20.2s remaining: 37.9s
354: learn: 0.3003348 total: 20.2s remaining: 37.9s
355: learn: 0.3002358 total: 20.3s remaining: 37.8s
356: learn: 0.3001164 total: 20.3s remaining: 37.7s
357: learn: 0.2999192 total: 20.4s remaining: 37.7s
358: learn: 0.2998103 total: 20.4s remaining: 37.6s
359: learn: 0.2997276 total: 20.5s remaining: 37.5s
360: learn: 0.2996793 total: 20.5s remaining: 37.5s
361: learn: 0.2995056 total: 20.6s remaining: 37.4s
362: learn: 0.2992717 total: 20.6s remaining: 37.3s
363: learn: 0.2990515 total: 20.7s remaining: 37.3s
364: learn: 0.2988934 total: 20.7s remaining: 37.2s
365: learn: 0.2986897 total: 20.8s remaining: 37.1s
366: learn: 0.2985376 total: 20.8s remaining: 37.1s
367: learn: 0.2984311 total: 20.9s remaining: 37s
368: learn: 0.2984066 total: 20.9s remaining: 36.9s
369: learn: 0.2982492 total: 21s remaining: 36.9s
370: learn: 0.2981355 total: 21s remaining: 36.8s
371: learn: 0.2979833 total: 21.1s remaining: 36.7s
372: learn: 0.2978873 total: 21.1s remaining: 36.6s
373: learn: 0.2978396 total: 21.2s remaining: 36.6s
374: learn: 0.2977945 total: 21.2s remaining: 36.5s
375: learn: 0.2977067 total: 21.3s remaining: 36.4s
376: learn: 0.2976139 total: 21.3s remaining: 36.4s
377: learn: 0.2974848 total: 21.4s remaining: 36.3s
378: learn: 0.2972562 total: 21.4s remaining: 36.2s
379: learn: 0.2970925 total: 21.5s remaining: 36.2s
380: learn: 0.2969711 total: 21.5s remaining: 36.1s
381: learn: 0.2969055 total: 21.6s remaining: 36s
382: learn: 0.2967740 total: 21.6s remaining: 36s
383: learn: 0.2965917 total: 21.7s remaining: 35.9s
384: learn: 0.2964866 total: 21.7s remaining: 35.8s
385: learn: 0.2964085 total: 21.8s remaining: 35.8s
386: learn: 0.2962668 total: 21.8s remaining: 35.7s
387: learn: 0.2961197 total: 21.9s remaining: 35.6s
388: learn: 0.2960359 total: 21.9s remaining: 35.6s
389: learn: 0.2958290 total: 22s remaining: 35.5s
390: learn: 0.2957517 total: 22s remaining: 35.4s
391: learn: 0.2956224 total: 22.1s remaining: 35.4s
392: learn: 0.2955949 total: 22.1s remaining: 35.3s
393: learn: 0.2953560 total: 22.2s remaining: 35.2s
394: learn: 0.2952593 total: 22.2s remaining: 35.2s
395: learn: 0.2952211 total: 22.3s remaining: 35.1s
396: learn: 0.2951596 total: 22.3s remaining: 35s
397: learn: 0.2951590 total: 22.3s remaining: 34.9s
398: learn: 0.2949921 total: 22.4s remaining: 34.9s
399: learn: 0.2948963 total: 22.5s remaining: 34.8s
400: learn: 0.2946754 total: 22.5s remaining: 34.7s
401: learn: 0.2945473 total: 22.6s remaining: 34.7s
402: learn: 0.2943738 total: 22.6s remaining: 34.6s
403: learn: 0.2942778 total: 22.7s remaining: 34.6s
404: learn: 0.2942051 total: 22.7s remaining: 34.5s
405: learn: 0.2940823 total: 22.8s remaining: 34.4s
406: learn: 0.2939721 total: 22.8s remaining: 34.4s
407: learn: 0.2938593 total: 22.9s remaining: 34.3s
408: learn: 0.2937321 total: 22.9s remaining: 34.2s
409: learn: 0.2936372 total: 23s remaining: 34.2s
410: learn: 0.2933924 total: 23s remaining: 34.1s
411: learn: 0.2932213 total: 23.1s remaining: 34s
412: learn: 0.2930860 total: 23.1s remaining: 34s
413: learn: 0.2930115 total: 23.2s remaining: 33.9s
414: learn: 0.2928547 total: 23.2s remaining: 33.9s
415: learn: 0.2927103 total: 23.3s remaining: 33.8s
416: learn: 0.2925911 total: 23.4s remaining: 33.8s
417: learn: 0.2924930 total: 23.4s remaining: 33.7s
418: learn: 0.2924929 total: 23.4s remaining: 33.6s
419: learn: 0.2922519 total: 23.5s remaining: 33.6s
420: learn: 0.2921355 total: 23.6s remaining: 33.5s
421: learn: 0.2919783 total: 23.6s remaining: 33.5s
422: learn: 0.2917631 total: 23.7s remaining: 33.4s
423: learn: 0.2915438 total: 23.8s remaining: 33.4s
424: learn: 0.2914860 total: 23.8s remaining: 33.3s
425: learn: 0.2913936 total: 23.9s remaining: 33.3s
426: learn: 0.2913289 total: 23.9s remaining: 33.3s
427: learn: 0.2911161 total: 24s remaining: 33.2s
428: learn: 0.2909729 total: 24.1s remaining: 33.2s
429: learn: 0.2908965 total: 24.1s remaining: 33.1s
430: learn: 0.2907857 total: 24.2s remaining: 33.1s
431: learn: 0.2906645 total: 24.2s remaining: 33s
432: learn: 0.2905179 total: 24.3s remaining: 33s
433: learn: 0.2904278 total: 24.4s remaining: 32.9s
434: learn: 0.2902778 total: 24.4s remaining: 32.9s
435: learn: 0.2901955 total: 24.5s remaining: 32.8s
436: learn: 0.2900951 total: 24.6s remaining: 32.8s
437: learn: 0.2900005 total: 24.6s remaining: 32.7s
438: learn: 0.2899107 total: 24.7s remaining: 32.7s
439: learn: 0.2898611 total: 24.7s remaining: 32.6s
440: learn: 0.2897926 total: 24.8s remaining: 32.6s
441: learn: 0.2895331 total: 24.9s remaining: 32.5s
442: learn: 0.2894337 total: 24.9s remaining: 32.5s
443: learn: 0.2892898 total: 25s remaining: 32.4s
444: learn: 0.2891699 total: 25.1s remaining: 32.4s
445: learn: 0.2890656 total: 25.1s remaining: 32.3s
446: learn: 0.2889233 total: 25.2s remaining: 32.3s
447: learn: 0.2888660 total: 25.2s remaining: 32.2s
448: learn: 0.2887120 total: 25.3s remaining: 32.2s
449: learn: 0.2884824 total: 25.4s remaining: 32.1s
450: learn: 0.2883929 total: 25.4s remaining: 32.1s
451: learn: 0.2882376 total: 25.5s remaining: 32s
452: learn: 0.2880558 total: 25.5s remaining: 32s
453: learn: 0.2879590 total: 25.6s remaining: 31.9s
454: learn: 0.2879588 total: 25.6s remaining: 31.8s
455: learn: 0.2878752 total: 25.7s remaining: 31.8s
456: learn: 0.2877712 total: 25.8s remaining: 31.7s
457: learn: 0.2875825 total: 25.8s remaining: 31.7s
458: learn: 0.2874759 total: 25.9s remaining: 31.6s
459: learn: 0.2874343 total: 25.9s remaining: 31.6s
460: learn: 0.2873107 total: 26s remaining: 31.5s
461: learn: 0.2871821 total: 26.1s remaining: 31.5s
462: learn: 0.2870133 total: 26.1s remaining: 31.4s
463: learn: 0.2869379 total: 26.2s remaining: 31.4s
464: learn: 0.2868816 total: 26.3s remaining: 31.3s
465: learn: 0.2868010 total: 26.3s remaining: 31.3s
466: learn: 0.2867564 total: 26.4s remaining: 31.2s
467: learn: 0.2866307 total: 26.4s remaining: 31.2s
468: learn: 0.2865672 total: 26.5s remaining: 31.1s
469: learn: 0.2863236 total: 26.6s remaining: 31.1s
470: learn: 0.2860856 total: 26.6s remaining: 31s
471: learn: 0.2859685 total: 26.7s remaining: 31s
472: learn: 0.2858467 total: 26.7s remaining: 30.9s
473: learn: 0.2857856 total: 26.8s remaining: 30.8s
474: learn: 0.2856513 total: 26.8s remaining: 30.8s
475: learn: 0.2855846 total: 26.9s remaining: 30.7s
476: learn: 0.2855213 total: 26.9s remaining: 30.6s
477: learn: 0.2854194 total: 27s remaining: 30.6s
478: learn: 0.2852906 total: 27s remaining: 30.5s
479: learn: 0.2852045 total: 27.1s remaining: 30.4s
480: learn: 0.2850281 total: 27.1s remaining: 30.4s
481: learn: 0.2849625 total: 27.2s remaining: 30.3s
482: learn: 0.2848313 total: 27.2s remaining: 30.3s
483: learn: 0.2847396 total: 27.3s remaining: 30.2s
484: learn: 0.2845632 total: 27.3s remaining: 30.1s
485: learn: 0.2844079 total: 27.4s remaining: 30.1s
486: learn: 0.2841714 total: 27.4s remaining: 30s
487: learn: 0.2839486 total: 27.5s remaining: 29.9s
488: learn: 0.2838728 total: 27.5s remaining: 29.9s
489: learn: 0.2838217 total: 27.6s remaining: 29.8s
490: learn: 0.2837494 total: 27.6s remaining: 29.8s
491: learn: 0.2836782 total: 27.7s remaining: 29.7s
492: learn: 0.2836055 total: 27.7s remaining: 29.6s
493: learn: 0.2835200 total: 27.8s remaining: 29.6s
494: learn: 0.2833761 total: 27.8s remaining: 29.5s
495: learn: 0.2833093 total: 27.9s remaining: 29.5s
496: learn: 0.2831591 total: 27.9s remaining: 29.4s
497: learn: 0.2830939 total: 28s remaining: 29.3s
498: learn: 0.2830341 total: 28s remaining: 29.3s
499: learn: 0.2829937 total: 28.1s remaining: 29.2s
500: learn: 0.2828900 total: 28.1s remaining: 29.1s
501: learn: 0.2827519 total: 28.2s remaining: 29.1s
502: learn: 0.2826468 total: 28.2s remaining: 29s
503: learn: 0.2825123 total: 28.3s remaining: 29s
504: learn: 0.2824257 total: 28.3s remaining: 28.9s
505: learn: 0.2824256 total: 28.4s remaining: 28.8s
506: learn: 0.2823151 total: 28.4s remaining: 28.7s
507: learn: 0.2820749 total: 28.5s remaining: 28.7s
508: learn: 0.2820028 total: 28.5s remaining: 28.6s
509: learn: 0.2818793 total: 28.6s remaining: 28.6s
510: learn: 0.2817343 total: 28.6s remaining: 28.5s
511: learn: 0.2816655 total: 28.7s remaining: 28.4s
512: learn: 0.2815015 total: 28.7s remaining: 28.4s
513: learn: 0.2815006 total: 28.7s remaining: 28.3s
514: learn: 0.2813496 total: 28.8s remaining: 28.2s
515: learn: 0.2813496 total: 28.8s remaining: 28.1s
516: learn: 0.2812741 total: 28.8s remaining: 28.1s
517: learn: 0.2812525 total: 28.9s remaining: 28s
518: learn: 0.2811678 total: 29s remaining: 28s
519: learn: 0.2810342 total: 29s remaining: 27.9s
520: learn: 0.2809239 total: 29.1s remaining: 27.8s
521: learn: 0.2808489 total: 29.1s remaining: 27.8s
522: learn: 0.2808087 total: 29.2s remaining: 27.7s
523: learn: 0.2807291 total: 29.2s remaining: 27.6s
524: learn: 0.2805976 total: 29.3s remaining: 27.6s
525: learn: 0.2804700 total: 29.3s remaining: 27.5s
526: learn: 0.2803633 total: 29.4s remaining: 27.5s
527: learn: 0.2803050 total: 29.4s remaining: 27.4s
528: learn: 0.2802962 total: 29.5s remaining: 27.3s
529: learn: 0.2801938 total: 29.5s remaining: 27.3s
530: learn: 0.2801937 total: 29.5s remaining: 27.2s
531: learn: 0.2801236 total: 29.6s remaining: 27.1s
532: learn: 0.2800006 total: 29.6s remaining: 27.1s
533: learn: 0.2800002 total: 29.7s remaining: 27s
534: learn: 0.2799651 total: 29.7s remaining: 26.9s
535: learn: 0.2799344 total: 29.8s remaining: 26.9s
536: learn: 0.2798329 total: 29.8s remaining: 26.8s
537: learn: 0.2797348 total: 29.9s remaining: 26.8s
538: learn: 0.2796450 total: 29.9s remaining: 26.7s
539: learn: 0.2795998 total: 30s remaining: 26.6s
540: learn: 0.2794414 total: 30s remaining: 26.6s
541: learn: 0.2793943 total: 30.1s remaining: 26.5s
542: learn: 0.2793812 total: 30.1s remaining: 26.5s
543: learn: 0.2791566 total: 30.2s remaining: 26.4s
544: learn: 0.2790089 total: 30.3s remaining: 26.4s
545: learn: 0.2789035 total: 30.3s remaining: 26.3s
546: learn: 0.2787981 total: 30.4s remaining: 26.3s
547: learn: 0.2787821 total: 30.4s remaining: 26.2s
548: learn: 0.2785509 total: 30.5s remaining: 26.2s
549: learn: 0.2784795 total: 30.6s remaining: 26.1s
550: learn: 0.2783626 total: 30.6s remaining: 26.1s
551: learn: 0.2783575 total: 30.7s remaining: 26s
552: learn: 0.2782593 total: 30.7s remaining: 26s
553: learn: 0.2780317 total: 30.8s remaining: 25.9s
554: learn: 0.2779588 total: 30.9s remaining: 25.9s
555: learn: 0.2778757 total: 30.9s remaining: 25.8s
556: learn: 0.2778180 total: 31s remaining: 25.8s
557: learn: 0.2777177 total: 31.1s remaining: 25.7s
558: learn: 0.2776695 total: 31.1s remaining: 25.7s
559: learn: 0.2775889 total: 31.2s remaining: 25.6s
560: learn: 0.2775239 total: 31.3s remaining: 25.6s
561: learn: 0.2774640 total: 31.3s remaining: 25.5s
562: learn: 0.2773684 total: 31.4s remaining: 25.5s
563: learn: 0.2772593 total: 31.4s remaining: 25.4s
564: learn: 0.2771796 total: 31.5s remaining: 25.4s
565: learn: 0.2770667 total: 31.6s remaining: 25.3s
566: learn: 0.2769747 total: 31.6s remaining: 25.3s
567: learn: 0.2768837 total: 31.7s remaining: 25.2s
568: learn: 0.2768101 total: 31.8s remaining: 25.2s
569: learn: 0.2766121 total: 31.8s remaining: 25.1s
570: learn: 0.2765512 total: 31.9s remaining: 25.1s
571: learn: 0.2765406 total: 31.9s remaining: 25s
572: learn: 0.2764623 total: 32s remaining: 25s
573: learn: 0.2763313 total: 32.1s remaining: 24.9s
574: learn: 0.2762259 total: 32.1s remaining: 24.9s
575: learn: 0.2761216 total: 32.2s remaining: 24.8s
576: learn: 0.2760999 total: 32.3s remaining: 24.8s
577: learn: 0.2760437 total: 32.3s remaining: 24.7s
578: learn: 0.2759421 total: 32.4s remaining: 24.7s
579: learn: 0.2759420 total: 32.4s remaining: 24.6s
580: learn: 0.2758364 total: 32.5s remaining: 24.5s
581: learn: 0.2756993 total: 32.5s remaining: 24.5s
582: learn: 0.2756252 total: 32.6s remaining: 24.4s
583: learn: 0.2755773 total: 32.7s remaining: 24.4s
584: learn: 0.2754131 total: 32.7s remaining: 24.3s
585: learn: 0.2752185 total: 32.8s remaining: 24.3s
586: learn: 0.2751070 total: 32.8s remaining: 24.2s
587: learn: 0.2750347 total: 32.9s remaining: 24.2s
588: learn: 0.2749506 total: 33s remaining: 24.1s
589: learn: 0.2747986 total: 33s remaining: 24.1s
590: learn: 0.2747744 total: 33.1s remaining: 24s
591: learn: 0.2746020 total: 33.2s remaining: 24s
592: learn: 0.2745105 total: 33.2s remaining: 23.9s
593: learn: 0.2744696 total: 33.3s remaining: 23.9s
594: learn: 0.2744025 total: 33.3s remaining: 23.8s
595: learn: 0.2743159 total: 33.4s remaining: 23.8s
596: learn: 0.2741609 total: 33.5s remaining: 23.7s
597: learn: 0.2740955 total: 33.5s remaining: 23.6s
598: learn: 0.2739866 total: 33.6s remaining: 23.6s
599: learn: 0.2739332 total: 33.6s remaining: 23.5s
600: learn: 0.2738516 total: 33.7s remaining: 23.5s
601: learn: 0.2738515 total: 33.7s remaining: 23.4s
602: learn: 0.2737313 total: 33.7s remaining: 23.3s
603: learn: 0.2736533 total: 33.8s remaining: 23.3s
604: learn: 0.2736356 total: 33.8s remaining: 23.2s
605: learn: 0.2735852 total: 33.9s remaining: 23.1s
606: learn: 0.2734694 total: 33.9s remaining: 23.1s
607: learn: 0.2733906 total: 34s remaining: 23s
608: learn: 0.2733436 total: 34s remaining: 23s
609: learn: 0.2732879 total: 34.1s remaining: 22.9s
610: learn: 0.2732472 total: 34.1s remaining: 22.8s
611: learn: 0.2731323 total: 34.2s remaining: 22.8s
612: learn: 0.2731245 total: 34.2s remaining: 22.7s
613: learn: 0.2730228 total: 34.3s remaining: 22.7s
614: learn: 0.2729189 total: 34.3s remaining: 22.6s
615: learn: 0.2728761 total: 34.4s remaining: 22.5s
616: learn: 0.2728028 total: 34.4s remaining: 22.5s
617: learn: 0.2727022 total: 34.5s remaining: 22.4s
618: learn: 0.2726475 total: 34.5s remaining: 22.4s
619: learn: 0.2725206 total: 34.6s remaining: 22.3s
620: learn: 0.2724229 total: 34.6s remaining: 22.2s
621: learn: 0.2723407 total: 34.7s remaining: 22.2s
622: learn: 0.2723171 total: 34.7s remaining: 22.1s
623: learn: 0.2723168 total: 34.8s remaining: 22.1s
624: learn: 0.2722136 total: 34.8s remaining: 22s
625: learn: 0.2722136 total: 34.8s remaining: 21.9s
626: learn: 0.2720745 total: 34.9s remaining: 21.9s
627: learn: 0.2719751 total: 34.9s remaining: 21.8s
628: learn: 0.2719751 total: 34.9s remaining: 21.7s
629: learn: 0.2717552 total: 35s remaining: 21.7s
630: learn: 0.2716660 total: 35s remaining: 21.6s
631: learn: 0.2715814 total: 35.1s remaining: 21.5s
632: learn: 0.2715346 total: 35.1s remaining: 21.5s
633: learn: 0.2714807 total: 35.2s remaining: 21.4s
634: learn: 0.2714368 total: 35.2s remaining: 21.4s
635: learn: 0.2713445 total: 35.3s remaining: 21.3s
636: learn: 0.2712848 total: 35.3s remaining: 21.3s
637: learn: 0.2712526 total: 35.4s remaining: 21.2s
638: learn: 0.2712525 total: 35.4s remaining: 21.1s
639: learn: 0.2712525 total: 35.4s remaining: 21s
640: learn: 0.2711652 total: 35.5s remaining: 21s
641: learn: 0.2711217 total: 35.5s remaining: 20.9s
642: learn: 0.2710435 total: 35.6s remaining: 20.9s
643: learn: 0.2709660 total: 35.6s remaining: 20.8s
644: learn: 0.2708303 total: 35.7s remaining: 20.7s
645: learn: 0.2707413 total: 35.7s remaining: 20.7s
646: learn: 0.2707183 total: 35.8s remaining: 20.6s
647: learn: 0.2706386 total: 35.8s remaining: 20.6s
648: learn: 0.2705763 total: 35.9s remaining: 20.5s
649: learn: 0.2705441 total: 35.9s remaining: 20.4s
650: learn: 0.2705046 total: 36s remaining: 20.4s
651: learn: 0.2705046 total: 36s remaining: 20.3s
652: learn: 0.2704508 total: 36s remaining: 20.3s
653: learn: 0.2703418 total: 36.1s remaining: 20.2s
654: learn: 0.2703416 total: 36.1s remaining: 20.1s
655: learn: 0.2703184 total: 36.2s remaining: 20.1s
656: learn: 0.2703112 total: 36.2s remaining: 20s
657: learn: 0.2701824 total: 36.3s remaining: 20s
658: learn: 0.2700998 total: 36.3s remaining: 19.9s
659: learn: 0.2698803 total: 36.4s remaining: 19.8s
660: learn: 0.2698265 total: 36.4s remaining: 19.8s
661: learn: 0.2697982 total: 36.5s remaining: 19.7s
662: learn: 0.2696226 total: 36.5s remaining: 19.7s
663: learn: 0.2696226 total: 36.5s remaining: 19.6s
664: learn: 0.2696124 total: 36.6s remaining: 19.5s
665: learn: 0.2695333 total: 36.6s remaining: 19.5s
666: learn: 0.2694420 total: 36.7s remaining: 19.4s
667: learn: 0.2694419 total: 36.7s remaining: 19.3s
668: learn: 0.2693729 total: 36.8s remaining: 19.3s
669: learn: 0.2692804 total: 36.8s remaining: 19.2s
670: learn: 0.2692689 total: 36.9s remaining: 19.2s
671: learn: 0.2691545 total: 36.9s remaining: 19.1s
672: learn: 0.2690548 total: 37s remaining: 19.1s
673: learn: 0.2689740 total: 37.1s remaining: 19s
674: learn: 0.2689016 total: 37.1s remaining: 19s
675: learn: 0.2688103 total: 37.2s remaining: 18.9s
676: learn: 0.2687537 total: 37.2s remaining: 18.9s
677: learn: 0.2686547 total: 37.3s remaining: 18.8s
678: learn: 0.2686292 total: 37.4s remaining: 18.8s
679: learn: 0.2686115 total: 37.4s remaining: 18.7s
680: learn: 0.2685615 total: 37.5s remaining: 18.7s
681: learn: 0.2685081 total: 37.6s remaining: 18.6s
682: learn: 0.2685008 total: 37.6s remaining: 18.6s
683: learn: 0.2684026 total: 37.7s remaining: 18.5s
684: learn: 0.2682733 total: 37.7s remaining: 18.5s
685: learn: 0.2682732 total: 37.8s remaining: 18.4s
686: learn: 0.2682494 total: 37.8s remaining: 18.3s
687: learn: 0.2682208 total: 37.9s remaining: 18.3s
688: learn: 0.2681451 total: 37.9s remaining: 18.2s
689: learn: 0.2679993 total: 38s remaining: 18.2s
690: learn: 0.2679531 total: 38.1s remaining: 18.1s
691: learn: 0.2678487 total: 38.1s remaining: 18.1s
692: learn: 0.2678100 total: 38.2s remaining: 18s
693: learn: 0.2677672 total: 38.2s remaining: 18s
694: learn: 0.2677398 total: 38.3s remaining: 17.9s
695: learn: 0.2676904 total: 38.4s remaining: 17.9s
696: learn: 0.2675312 total: 38.4s remaining: 17.8s
697: learn: 0.2675311 total: 38.5s remaining: 17.7s
698: learn: 0.2674108 total: 38.5s remaining: 17.7s
699: learn: 0.2673634 total: 38.6s remaining: 17.6s
700: learn: 0.2673124 total: 38.6s remaining: 17.6s
701: learn: 0.2672174 total: 38.7s remaining: 17.5s
702: learn: 0.2672147 total: 38.7s remaining: 17.5s
703: learn: 0.2669665 total: 38.8s remaining: 17.4s
704: learn: 0.2669665 total: 38.8s remaining: 17.3s
705: learn: 0.2669664 total: 38.8s remaining: 17.3s
706: learn: 0.2669663 total: 38.9s remaining: 17.2s
707: learn: 0.2667962 total: 38.9s remaining: 17.2s
708: learn: 0.2667124 total: 39s remaining: 17.1s
709: learn: 0.2666584 total: 39.1s remaining: 17.1s
710: learn: 0.2665676 total: 39.1s remaining: 17s
711: learn: 0.2664823 total: 39.2s remaining: 16.9s
712: learn: 0.2663090 total: 39.2s remaining: 16.9s
713: learn: 0.2662428 total: 39.3s remaining: 16.8s
714: learn: 0.2661999 total: 39.4s remaining: 16.8s
715: learn: 0.2660740 total: 39.4s remaining: 16.7s
716: learn: 0.2660281 total: 39.5s remaining: 16.7s
717: learn: 0.2659599 total: 39.6s remaining: 16.6s
718: learn: 0.2659094 total: 39.6s remaining: 16.6s
719: learn: 0.2658045 total: 39.7s remaining: 16.5s
720: learn: 0.2657723 total: 39.7s remaining: 16.5s
721: learn: 0.2656683 total: 39.8s remaining: 16.4s
722: learn: 0.2656179 total: 39.9s remaining: 16.4s
723: learn: 0.2655506 total: 39.9s remaining: 16.3s
724: learn: 0.2655408 total: 40s remaining: 16.3s
725: learn: 0.2655291 total: 40s remaining: 16.2s
726: learn: 0.2654679 total: 40.1s remaining: 16.2s
727: learn: 0.2653112 total: 40.2s remaining: 16.1s
728: learn: 0.2652098 total: 40.2s remaining: 16.1s
729: learn: 0.2651652 total: 40.3s remaining: 16s
730: learn: 0.2651647 total: 40.3s remaining: 15.9s
731: learn: 0.2651032 total: 40.4s remaining: 15.9s
732: learn: 0.2650648 total: 40.4s remaining: 15.8s
733: learn: 0.2648997 total: 40.5s remaining: 15.8s
734: learn: 0.2648996 total: 40.5s remaining: 15.7s
735: learn: 0.2648663 total: 40.5s remaining: 15.6s
736: learn: 0.2648663 total: 40.6s remaining: 15.6s
737: learn: 0.2646984 total: 40.6s remaining: 15.5s
738: learn: 0.2646945 total: 40.7s remaining: 15.5s
739: learn: 0.2646867 total: 40.7s remaining: 15.4s
740: learn: 0.2646689 total: 40.8s remaining: 15.4s
741: learn: 0.2646689 total: 40.8s remaining: 15.3s
742: learn: 0.2646555 total: 40.8s remaining: 15.2s
743: learn: 0.2646169 total: 40.9s remaining: 15.2s
744: learn: 0.2646169 total: 40.9s remaining: 15.1s
745: learn: 0.2646169 total: 40.9s remaining: 15s
746: learn: 0.2645182 total: 41s remaining: 15s
747: learn: 0.2644577 total: 41s remaining: 14.9s
748: learn: 0.2643677 total: 41.1s remaining: 14.9s
749: learn: 0.2642733 total: 41.1s remaining: 14.8s
750: learn: 0.2642733 total: 41.1s remaining: 14.7s
751: learn: 0.2641949 total: 41.2s remaining: 14.7s
752: learn: 0.2640870 total: 41.3s remaining: 14.6s
753: learn: 0.2640618 total: 41.3s remaining: 14.6s
754: learn: 0.2639038 total: 41.4s remaining: 14.5s
755: learn: 0.2638588 total: 41.4s remaining: 14.5s
756: learn: 0.2637254 total: 41.5s remaining: 14.4s
757: learn: 0.2636816 total: 41.5s remaining: 14.3s
758: learn: 0.2636398 total: 41.6s remaining: 14.3s
759: learn: 0.2635846 total: 41.6s remaining: 14.2s
760: learn: 0.2634900 total: 41.7s remaining: 14.2s
761: learn: 0.2634896 total: 41.7s remaining: 14.1s
762: learn: 0.2633983 total: 41.7s remaining: 14.1s
763: learn: 0.2632643 total: 41.8s remaining: 14s
764: learn: 0.2632114 total: 41.8s remaining: 13.9s
765: learn: 0.2630653 total: 41.9s remaining: 13.9s
766: learn: 0.2630653 total: 41.9s remaining: 13.8s
767: learn: 0.2630651 total: 41.9s remaining: 13.8s
768: learn: 0.2629962 total: 42s remaining: 13.7s
769: learn: 0.2628784 total: 42s remaining: 13.6s
770: learn: 0.2628019 total: 42.1s remaining: 13.6s
771: learn: 0.2628018 total: 42.1s remaining: 13.5s
772: learn: 0.2627801 total: 42.1s remaining: 13.5s
773: learn: 0.2627088 total: 42.2s remaining: 13.4s
774: learn: 0.2626237 total: 42.2s remaining: 13.4s
775: learn: 0.2626191 total: 42.3s remaining: 13.3s
776: learn: 0.2626191 total: 42.3s remaining: 13.2s
777: learn: 0.2626074 total: 42.4s remaining: 13.2s
778: learn: 0.2626073 total: 42.4s remaining: 13.1s
779: learn: 0.2625333 total: 42.4s remaining: 13.1s
780: learn: 0.2624368 total: 42.5s remaining: 13s
781: learn: 0.2624325 total: 42.5s remaining: 12.9s
782: learn: 0.2624320 total: 42.5s remaining: 12.9s
783: learn: 0.2624320 total: 42.6s remaining: 12.8s
784: learn: 0.2624319 total: 42.6s remaining: 12.7s
785: learn: 0.2624105 total: 42.6s remaining: 12.7s
786: learn: 0.2624104 total: 42.7s remaining: 12.6s
787: learn: 0.2623764 total: 42.7s remaining: 12.6s
788: learn: 0.2621381 total: 42.8s remaining: 12.5s
789: learn: 0.2621213 total: 42.8s remaining: 12.5s
790: learn: 0.2620450 total: 42.9s remaining: 12.4s
791: learn: 0.2619605 total: 42.9s remaining: 12.4s
792: learn: 0.2617959 total: 43s remaining: 12.3s
793: learn: 0.2617560 total: 43s remaining: 12.2s
794: learn: 0.2617153 total: 43.1s remaining: 12.2s
795: learn: 0.2616921 total: 43.1s remaining: 12.1s
796: learn: 0.2616420 total: 43.2s remaining: 12.1s
797: learn: 0.2616047 total: 43.2s remaining: 12s
798: learn: 0.2615605 total: 43.3s remaining: 12s
799: learn: 0.2613713 total: 43.3s remaining: 11.9s
800: learn: 0.2613356 total: 43.4s remaining: 11.9s
801: learn: 0.2613109 total: 43.4s remaining: 11.8s
802: learn: 0.2612239 total: 43.5s remaining: 11.7s
803: learn: 0.2610949 total: 43.5s remaining: 11.7s
804: learn: 0.2610417 total: 43.6s remaining: 11.6s
805: learn: 0.2608957 total: 43.6s remaining: 11.6s
806: learn: 0.2608508 total: 43.7s remaining: 11.5s
807: learn: 0.2608244 total: 43.7s remaining: 11.5s
808: learn: 0.2608137 total: 43.8s remaining: 11.4s
809: learn: 0.2607922 total: 43.9s remaining: 11.4s
810: learn: 0.2607189 total: 43.9s remaining: 11.3s
811: learn: 0.2607153 total: 44s remaining: 11.3s
812: learn: 0.2607086 total: 44s remaining: 11.2s
813: learn: 0.2606795 total: 44.1s remaining: 11.2s
814: learn: 0.2605345 total: 44.2s remaining: 11.1s
815: learn: 0.2604349 total: 44.2s remaining: 11.1s
816: learn: 0.2603943 total: 44.3s remaining: 11s
817: learn: 0.2603943 total: 44.3s remaining: 10.9s
818: learn: 0.2603729 total: 44.4s remaining: 10.9s
819: learn: 0.2603632 total: 44.4s remaining: 10.8s
820: learn: 0.2602452 total: 44.5s remaining: 10.8s
821: learn: 0.2602450 total: 44.5s remaining: 10.7s
822: learn: 0.2602448 total: 44.6s remaining: 10.7s
823: learn: 0.2602124 total: 44.6s remaining: 10.6s
824: learn: 0.2601488 total: 44.7s remaining: 10.6s
825: learn: 0.2600754 total: 44.8s remaining: 10.5s
826: learn: 0.2600753 total: 44.8s remaining: 10.4s
827: learn: 0.2600547 total: 44.8s remaining: 10.4s
828: learn: 0.2600240 total: 44.9s remaining: 10.3s
829: learn: 0.2599941 total: 45s remaining: 10.3s
830: learn: 0.2599144 total: 45s remaining: 10.2s
831: learn: 0.2599143 total: 45.1s remaining: 10.2s
832: learn: 0.2598491 total: 45.1s remaining: 10.1s
833: learn: 0.2598090 total: 45.2s remaining: 10.1s
834: learn: 0.2597857 total: 45.2s remaining: 10s
835: learn: 0.2597386 total: 45.3s remaining: 9.97s
836: learn: 0.2597230 total: 45.4s remaining: 9.92s
837: learn: 0.2597230 total: 45.4s remaining: 9.86s
838: learn: 0.2596793 total: 45.5s remaining: 9.8s
839: learn: 0.2594914 total: 45.5s remaining: 9.76s
840: learn: 0.2594531 total: 45.6s remaining: 9.7s
841: learn: 0.2594413 total: 45.6s remaining: 9.65s
842: learn: 0.2592826 total: 45.7s remaining: 9.6s
843: learn: 0.2592568 total: 45.8s remaining: 9.55s
844: learn: 0.2591505 total: 45.8s remaining: 9.49s
845: learn: 0.2591365 total: 45.9s remaining: 9.44s
846: learn: 0.2590511 total: 46s remaining: 9.39s
847: learn: 0.2590009 total: 46s remaining: 9.33s
848: learn: 0.2589347 total: 46.1s remaining: 9.28s
849: learn: 0.2589005 total: 46.1s remaining: 9.23s
850: learn: 0.2588460 total: 46.2s remaining: 9.18s
851: learn: 0.2587871 total: 46.3s remaining: 9.12s
852: learn: 0.2587375 total: 46.3s remaining: 9.07s
853: learn: 0.2587013 total: 46.4s remaining: 9.02s
854: learn: 0.2585859 total: 46.4s remaining: 8.96s
855: learn: 0.2584968 total: 46.5s remaining: 8.91s
856: learn: 0.2584459 total: 46.6s remaining: 8.86s
857: learn: 0.2584454 total: 46.6s remaining: 8.8s
858: learn: 0.2584170 total: 46.7s remaining: 8.75s
859: learn: 0.2583538 total: 46.7s remaining: 8.7s
860: learn: 0.2583312 total: 46.8s remaining: 8.64s
861: learn: 0.2582932 total: 46.9s remaining: 8.59s
862: learn: 0.2582801 total: 46.9s remaining: 8.54s
863: learn: 0.2580752 total: 47s remaining: 8.48s
864: learn: 0.2579840 total: 47.1s remaining: 8.43s
865: learn: 0.2579392 total: 47.1s remaining: 8.38s
866: learn: 0.2578846 total: 47.2s remaining: 8.32s
867: learn: 0.2578642 total: 47.2s remaining: 8.27s
868: learn: 0.2577945 total: 47.3s remaining: 8.21s
869: learn: 0.2577591 total: 47.3s remaining: 8.16s
870: learn: 0.2576752 total: 47.4s remaining: 8.1s
871: learn: 0.2575659 total: 47.4s remaining: 8.05s
872: learn: 0.2574684 total: 47.5s remaining: 7.99s
873: learn: 0.2574568 total: 47.5s remaining: 7.94s
874: learn: 0.2573974 total: 47.6s remaining: 7.88s
875: learn: 0.2573165 total: 47.6s remaining: 7.83s
876: learn: 0.2572896 total: 47.7s remaining: 7.77s
877: learn: 0.2572586 total: 47.7s remaining: 7.72s
878: learn: 0.2571228 total: 47.8s remaining: 7.66s
879: learn: 0.2570681 total: 47.8s remaining: 7.61s
880: learn: 0.2570656 total: 47.9s remaining: 7.55s
881: learn: 0.2569933 total: 47.9s remaining: 7.5s
882: learn: 0.2568392 total: 48s remaining: 7.44s
883: learn: 0.2568386 total: 48s remaining: 7.39s
884: learn: 0.2568385 total: 48s remaining: 7.33s
885: learn: 0.2568007 total: 48.1s remaining: 7.27s
886: learn: 0.2567937 total: 48.1s remaining: 7.22s
887: learn: 0.2567452 total: 48.2s remaining: 7.16s
888: learn: 0.2567452 total: 48.2s remaining: 7.1s
889: learn: 0.2567375 total: 48.3s remaining: 7.05s
890: learn: 0.2567158 total: 48.3s remaining: 7s
891: learn: 0.2566724 total: 48.4s remaining: 6.94s
892: learn: 0.2566348 total: 48.4s remaining: 6.89s
893: learn: 0.2563817 total: 48.5s remaining: 6.83s
894: learn: 0.2563815 total: 48.5s remaining: 6.77s
895: learn: 0.2563812 total: 48.5s remaining: 6.72s
896: learn: 0.2563591 total: 48.6s remaining: 6.66s
897: learn: 0.2562396 total: 48.6s remaining: 6.61s
898: learn: 0.2561853 total: 48.7s remaining: 6.55s
899: learn: 0.2560716 total: 48.7s remaining: 6.5s
900: learn: 0.2559419 total: 48.8s remaining: 6.45s
901: learn: 0.2559114 total: 48.8s remaining: 6.39s
902: learn: 0.2558832 total: 48.9s remaining: 6.33s
903: learn: 0.2558771 total: 48.9s remaining: 6.28s
904: learn: 0.2557200 total: 49s remaining: 6.23s
905: learn: 0.2556950 total: 49s remaining: 6.17s
906: learn: 0.2556355 total: 49.1s remaining: 6.12s
907: learn: 0.2556341 total: 49.1s remaining: 6.06s
908: learn: 0.2556134 total: 49.2s remaining: 6.01s
909: learn: 0.2556120 total: 49.2s remaining: 5.95s
910: learn: 0.2555719 total: 49.3s remaining: 5.89s
911: learn: 0.2555276 total: 49.3s remaining: 5.84s
912: learn: 0.2554413 total: 49.4s remaining: 5.79s
913: learn: 0.2553981 total: 49.4s remaining: 5.73s
914: learn: 0.2553896 total: 49.5s remaining: 5.68s
915: learn: 0.2553472 total: 49.5s remaining: 5.62s
916: learn: 0.2552869 total: 49.6s remaining: 5.57s
917: learn: 0.2552801 total: 49.6s remaining: 5.51s
918: learn: 0.2552775 total: 49.7s remaining: 5.46s
919: learn: 0.2552085 total: 49.7s remaining: 5.4s
920: learn: 0.2551511 total: 49.8s remaining: 5.35s
921: learn: 0.2551511 total: 49.8s remaining: 5.29s
922: learn: 0.2550817 total: 49.8s remaining: 5.24s
923: learn: 0.2549750 total: 49.9s remaining: 5.18s
924: learn: 0.2549077 total: 49.9s remaining: 5.13s
925: learn: 0.2548680 total: 50s remaining: 5.07s
926: learn: 0.2548426 total: 50s remaining: 5.02s
927: learn: 0.2548210 total: 50.1s remaining: 4.97s
928: learn: 0.2548210 total: 50.1s remaining: 4.91s
929: learn: 0.2547645 total: 50.2s remaining: 4.85s
930: learn: 0.2547391 total: 50.2s remaining: 4.8s
931: learn: 0.2547386 total: 50.3s remaining: 4.75s
932: learn: 0.2547223 total: 50.3s remaining: 4.69s
933: learn: 0.2546981 total: 50.4s remaining: 4.64s
934: learn: 0.2546409 total: 50.4s remaining: 4.58s
935: learn: 0.2545848 total: 50.5s remaining: 4.53s
936: learn: 0.2545107 total: 50.5s remaining: 4.47s
937: learn: 0.2544494 total: 50.5s remaining: 4.42s
938: learn: 0.2543836 total: 50.6s remaining: 4.37s
939: learn: 0.2542996 total: 50.7s remaining: 4.31s
940: learn: 0.2542512 total: 50.7s remaining: 4.26s
941: learn: 0.2542504 total: 50.8s remaining: 4.21s
942: learn: 0.2541727 total: 50.9s remaining: 4.15s
943: learn: 0.2540975 total: 50.9s remaining: 4.1s
944: learn: 0.2539948 total: 51s remaining: 4.05s
945: learn: 0.2539878 total: 51s remaining: 3.99s
946: learn: 0.2539307 total: 51.1s remaining: 3.94s
947: learn: 0.2539047 total: 51.2s remaining: 3.89s
948: learn: 0.2537639 total: 51.2s remaining: 3.83s
949: learn: 0.2537393 total: 51.3s remaining: 3.78s
950: learn: 0.2537194 total: 51.4s remaining: 3.73s
951: learn: 0.2536948 total: 51.4s remaining: 3.67s
952: learn: 0.2536947 total: 51.5s remaining: 3.62s
953: learn: 0.2536654 total: 51.5s remaining: 3.56s
954: learn: 0.2536258 total: 51.6s remaining: 3.51s
955: learn: 0.2535964 total: 51.6s remaining: 3.46s
956: learn: 0.2535469 total: 51.7s remaining: 3.4s
957: learn: 0.2534620 total: 51.8s remaining: 3.35s
958: learn: 0.2534514 total: 51.8s remaining: 3.29s
959: learn: 0.2534006 total: 51.9s remaining: 3.24s
960: learn: 0.2533790 total: 51.9s remaining: 3.19s
961: learn: 0.2532868 total: 52s remaining: 3.13s
962: learn: 0.2532853 total: 52s remaining: 3.08s
963: learn: 0.2531411 total: 52.1s remaining: 3.03s
964: learn: 0.2530392 total: 52.2s remaining: 2.97s
965: learn: 0.2530334 total: 52.2s remaining: 2.92s
966: learn: 0.2529237 total: 52.3s remaining: 2.87s
967: learn: 0.2529110 total: 52.4s remaining: 2.81s
968: learn: 0.2529104 total: 52.4s remaining: 2.76s
969: learn: 0.2529100 total: 52.4s remaining: 2.7s
970: learn: 0.2528619 total: 52.5s remaining: 2.65s
971: learn: 0.2528231 total: 52.6s remaining: 2.6s
972: learn: 0.2526652 total: 52.6s remaining: 2.54s
973: learn: 0.2524762 total: 52.7s remaining: 2.49s
974: learn: 0.2524636 total: 52.7s remaining: 2.43s
975: learn: 0.2524636 total: 52.8s remaining: 2.38s
976: learn: 0.2524160 total: 52.8s remaining: 2.33s
977: learn: 0.2523935 total: 52.9s remaining: 2.27s
978: learn: 0.2523353 total: 53s remaining: 2.22s
979: learn: 0.2522983 total: 53s remaining: 2.16s
980: learn: 0.2522278 total: 53.1s remaining: 2.11s
981: learn: 0.2521961 total: 53.1s remaining: 2.06s
982: learn: 0.2520850 total: 53.2s remaining: 2s
983: learn: 0.2520392 total: 53.3s remaining: 1.95s
984: learn: 0.2520028 total: 53.3s remaining: 1.89s
985: learn: 0.2519874 total: 53.4s remaining: 1.84s
986: learn: 0.2519620 total: 53.4s remaining: 1.79s
987: learn: 0.2519430 total: 53.5s remaining: 1.73s
988: learn: 0.2519254 total: 53.6s remaining: 1.68s
989: learn: 0.2518575 total: 53.6s remaining: 1.63s
990: learn: 0.2518158 total: 53.7s remaining: 1.57s
991: learn: 0.2518158 total: 53.7s remaining: 1.52s
992: learn: 0.2517971 total: 53.8s remaining: 1.46s
993: learn: 0.2517565 total: 53.9s remaining: 1.41s
994: learn: 0.2517472 total: 53.9s remaining: 1.35s
995: learn: 0.2516293 total: 54s remaining: 1.3s
996: learn: 0.2515990 total: 54s remaining: 1.25s
997: learn: 0.2515931 total: 54.1s remaining: 1.19s
998: learn: 0.2515813 total: 54.1s remaining: 1.14s
999: learn: 0.2515408 total: 54.2s remaining: 1.08s
1000: learn: 0.2514677 total: 54.2s remaining: 1.03s
1001: learn: 0.2514675 total: 54.3s remaining: 975ms
1002: learn: 0.2514220 total: 54.3s remaining: 921ms
1003: learn: 0.2514179 total: 54.4s remaining: 866ms
1004: learn: 0.2513818 total: 54.4s remaining: 812ms
1005: learn: 0.2513547 total: 54.5s remaining: 758ms
1006: learn: 0.2513162 total: 54.5s remaining: 704ms
1007: learn: 0.2513162 total: 54.5s remaining: 649ms
1008: learn: 0.2513046 total: 54.6s remaining: 595ms
1009: learn: 0.2512633 total: 54.6s remaining: 541ms
1010: learn: 0.2512115 total: 54.7s remaining: 487ms
1011: learn: 0.2512115 total: 54.7s remaining: 432ms
1012: learn: 0.2511996 total: 54.8s remaining: 378ms
1013: learn: 0.2511995 total: 54.8s remaining: 324ms
1014: learn: 0.2511149 total: 54.8s remaining: 270ms
1015: learn: 0.2510782 total: 54.9s remaining: 216ms
1016: learn: 0.2510781 total: 54.9s remaining: 162ms
1017: learn: 0.2510110 total: 55s remaining: 108ms
1018: learn: 0.2507562 total: 55s remaining: 54ms
1019: learn: 0.2506735 total: 55.1s remaining: 0us
Finished training fold 3 - running score 0.8629569513860679
Running fold 4, 15737 train samples, 2622 validation samples
0: learn: 0.6477005 total: 55.9ms remaining: 56.9s
1: learn: 0.6084783 total: 110ms remaining: 56.1s
2: learn: 0.5750049 total: 163ms remaining: 55.3s
3: learn: 0.5463218 total: 215ms remaining: 54.6s
4: learn: 0.5216885 total: 266ms remaining: 53.9s
5: learn: 0.5006334 total: 315ms remaining: 53.2s
6: learn: 0.4823764 total: 365ms remaining: 52.8s
7: learn: 0.4667397 total: 416ms remaining: 52.6s
8: learn: 0.4534634 total: 465ms remaining: 52.2s
9: learn: 0.4420665 total: 517ms remaining: 52.3s
10: learn: 0.4319177 total: 566ms remaining: 52s
11: learn: 0.4231283 total: 617ms remaining: 51.8s
12: learn: 0.4154736 total: 665ms remaining: 51.5s
13: learn: 0.4088598 total: 719ms remaining: 51.6s
14: learn: 0.4030358 total: 768ms remaining: 51.5s
15: learn: 0.3981051 total: 818ms remaining: 51.3s
16: learn: 0.3936335 total: 870ms remaining: 51.3s
17: learn: 0.3898218 total: 919ms remaining: 51.2s
18: learn: 0.3865365 total: 969ms remaining: 51s
19: learn: 0.3836728 total: 1.02s remaining: 50.9s
20: learn: 0.3810547 total: 1.07s remaining: 50.9s
21: learn: 0.3787251 total: 1.13s remaining: 51.1s
22: learn: 0.3766682 total: 1.18s remaining: 51.3s
23: learn: 0.3749066 total: 1.24s remaining: 51.3s
24: learn: 0.3733009 total: 1.29s remaining: 51.3s
25: learn: 0.3719597 total: 1.34s remaining: 51.1s
26: learn: 0.3707107 total: 1.39s remaining: 51s
27: learn: 0.3697132 total: 1.44s remaining: 50.8s
28: learn: 0.3687219 total: 1.49s remaining: 50.8s
29: learn: 0.3678646 total: 1.53s remaining: 50.6s
30: learn: 0.3670662 total: 1.58s remaining: 50.5s
31: learn: 0.3663362 total: 1.64s remaining: 50.6s
32: learn: 0.3656576 total: 1.69s remaining: 50.5s
33: learn: 0.3651504 total: 1.74s remaining: 50.5s
34: learn: 0.3646592 total: 1.79s remaining: 50.3s
35: learn: 0.3640811 total: 1.84s remaining: 50.3s
36: learn: 0.3636597 total: 1.89s remaining: 50.2s
37: learn: 0.3631974 total: 1.94s remaining: 50.1s
38: learn: 0.3628152 total: 1.99s remaining: 50s
39: learn: 0.3623342 total: 2.04s remaining: 50s
40: learn: 0.3620172 total: 2.09s remaining: 49.9s
41: learn: 0.3616753 total: 2.14s remaining: 49.8s
42: learn: 0.3612903 total: 2.19s remaining: 49.8s
43: learn: 0.3609204 total: 2.24s remaining: 49.8s
44: learn: 0.3606966 total: 2.29s remaining: 49.7s
45: learn: 0.3603657 total: 2.35s remaining: 49.7s
46: learn: 0.3600285 total: 2.39s remaining: 49.6s
47: learn: 0.3597381 total: 2.44s remaining: 49.5s
48: learn: 0.3594516 total: 2.49s remaining: 49.4s
49: learn: 0.3592884 total: 2.54s remaining: 49.3s
50: learn: 0.3590327 total: 2.59s remaining: 49.3s
51: learn: 0.3585475 total: 2.65s remaining: 49.3s
52: learn: 0.3583696 total: 2.7s remaining: 49.2s
53: learn: 0.3581232 total: 2.75s remaining: 49.1s
54: learn: 0.3580069 total: 2.79s remaining: 49s
55: learn: 0.3578146 total: 2.84s remaining: 49s
56: learn: 0.3575721 total: 2.89s remaining: 48.9s
57: learn: 0.3572914 total: 2.94s remaining: 48.8s
58: learn: 0.3571273 total: 2.99s remaining: 48.7s
59: learn: 0.3569437 total: 3.04s remaining: 48.7s
60: learn: 0.3567281 total: 3.09s remaining: 48.6s
61: learn: 0.3563993 total: 3.14s remaining: 48.5s
62: learn: 0.3561634 total: 3.19s remaining: 48.5s
63: learn: 0.3557982 total: 3.24s remaining: 48.4s
64: learn: 0.3554549 total: 3.29s remaining: 48.4s
65: learn: 0.3551955 total: 3.34s remaining: 48.3s
66: learn: 0.3550695 total: 3.4s remaining: 48.3s
67: learn: 0.3548334 total: 3.46s remaining: 48.4s
68: learn: 0.3544286 total: 3.52s remaining: 48.5s
69: learn: 0.3543219 total: 3.58s remaining: 48.6s
70: learn: 0.3541231 total: 3.64s remaining: 48.7s
71: learn: 0.3539814 total: 3.7s remaining: 48.8s
72: learn: 0.3536314 total: 3.76s remaining: 48.8s
73: learn: 0.3533534 total: 3.82s remaining: 48.9s
74: learn: 0.3531990 total: 3.88s remaining: 49s
75: learn: 0.3530301 total: 3.95s remaining: 49s
76: learn: 0.3527633 total: 4.01s remaining: 49.1s
77: learn: 0.3525990 total: 4.07s remaining: 49.1s
78: learn: 0.3522859 total: 4.13s remaining: 49.2s
79: learn: 0.3521072 total: 4.19s remaining: 49.2s
80: learn: 0.3519878 total: 4.25s remaining: 49.3s
81: learn: 0.3518387 total: 4.31s remaining: 49.3s
82: learn: 0.3516279 total: 4.37s remaining: 49.4s
83: learn: 0.3514673 total: 4.43s remaining: 49.4s
84: learn: 0.3512937 total: 4.5s remaining: 49.4s
85: learn: 0.3510197 total: 4.55s remaining: 49.5s
86: learn: 0.3508409 total: 4.62s remaining: 49.5s
87: learn: 0.3506797 total: 4.68s remaining: 49.6s
88: learn: 0.3504926 total: 4.74s remaining: 49.6s
89: learn: 0.3503500 total: 4.8s remaining: 49.6s
90: learn: 0.3500828 total: 4.87s remaining: 49.7s
91: learn: 0.3499198 total: 4.93s remaining: 49.7s
92: learn: 0.3497692 total: 4.99s remaining: 49.7s
93: learn: 0.3495662 total: 5.05s remaining: 49.8s
94: learn: 0.3494605 total: 5.12s remaining: 49.8s
95: learn: 0.3491075 total: 5.17s remaining: 49.8s
96: learn: 0.3489816 total: 5.23s remaining: 49.8s
97: learn: 0.3487568 total: 5.29s remaining: 49.8s
98: learn: 0.3486776 total: 5.36s remaining: 49.8s
99: learn: 0.3484707 total: 5.42s remaining: 49.9s
100: learn: 0.3483511 total: 5.49s remaining: 49.9s
101: learn: 0.3481782 total: 5.55s remaining: 50s
102: learn: 0.3480499 total: 5.61s remaining: 50s
103: learn: 0.3478246 total: 5.68s remaining: 50s
104: learn: 0.3476535 total: 5.74s remaining: 50s
105: learn: 0.3474421 total: 5.8s remaining: 50s
106: learn: 0.3472400 total: 5.86s remaining: 50s
107: learn: 0.3470722 total: 5.92s remaining: 50s
108: learn: 0.3468728 total: 5.98s remaining: 50s
109: learn: 0.3467480 total: 6.05s remaining: 50s
110: learn: 0.3465192 total: 6.11s remaining: 50s
111: learn: 0.3463255 total: 6.17s remaining: 50s
112: learn: 0.3462126 total: 6.23s remaining: 50s
113: learn: 0.3460252 total: 6.29s remaining: 50s
114: learn: 0.3457796 total: 6.35s remaining: 50s
115: learn: 0.3457042 total: 6.41s remaining: 50s
116: learn: 0.3455328 total: 6.48s remaining: 50s
117: learn: 0.3452975 total: 6.54s remaining: 50s
118: learn: 0.3451980 total: 6.6s remaining: 50s
119: learn: 0.3449792 total: 6.66s remaining: 50s
120: learn: 0.3448353 total: 6.72s remaining: 49.9s
121: learn: 0.3446504 total: 6.79s remaining: 50s
122: learn: 0.3444941 total: 6.83s remaining: 49.8s
123: learn: 0.3442502 total: 6.89s remaining: 49.8s
124: learn: 0.3439330 total: 6.94s remaining: 49.7s
125: learn: 0.3436819 total: 6.99s remaining: 49.6s
126: learn: 0.3434779 total: 7.04s remaining: 49.5s
127: learn: 0.3433457 total: 7.09s remaining: 49.4s
128: learn: 0.3432104 total: 7.14s remaining: 49.3s
129: learn: 0.3430565 total: 7.19s remaining: 49.2s
130: learn: 0.3428849 total: 7.24s remaining: 49.1s
131: learn: 0.3425409 total: 7.29s remaining: 49s
132: learn: 0.3423652 total: 7.33s remaining: 48.9s
133: learn: 0.3422780 total: 7.36s remaining: 48.7s
134: learn: 0.3420658 total: 7.41s remaining: 48.6s
135: learn: 0.3418486 total: 7.46s remaining: 48.5s
136: learn: 0.3416860 total: 7.51s remaining: 48.4s
137: learn: 0.3414437 total: 7.57s remaining: 48.4s
138: learn: 0.3413396 total: 7.61s remaining: 48.2s
139: learn: 0.3411813 total: 7.66s remaining: 48.2s
140: learn: 0.3409517 total: 7.71s remaining: 48.1s
141: learn: 0.3407872 total: 7.76s remaining: 48s
142: learn: 0.3406677 total: 7.81s remaining: 47.9s
143: learn: 0.3404959 total: 7.86s remaining: 47.8s
144: learn: 0.3402286 total: 7.91s remaining: 47.7s
145: learn: 0.3399541 total: 7.96s remaining: 47.7s
146: learn: 0.3396339 total: 8.01s remaining: 47.6s
147: learn: 0.3394077 total: 8.06s remaining: 47.5s
148: learn: 0.3393893 total: 8.08s remaining: 47.3s
149: learn: 0.3391791 total: 8.14s remaining: 47.2s
150: learn: 0.3391097 total: 8.19s remaining: 47.2s
151: learn: 0.3389603 total: 8.25s remaining: 47.1s
152: learn: 0.3388710 total: 8.3s remaining: 47s
153: learn: 0.3387836 total: 8.35s remaining: 47s
154: learn: 0.3386087 total: 8.4s remaining: 46.9s
155: learn: 0.3385885 total: 8.43s remaining: 46.7s
156: learn: 0.3385000 total: 8.48s remaining: 46.6s
157: learn: 0.3382624 total: 8.53s remaining: 46.5s
158: learn: 0.3380872 total: 8.58s remaining: 46.5s
159: learn: 0.3379811 total: 8.63s remaining: 46.4s
160: learn: 0.3378508 total: 8.69s remaining: 46.3s
161: learn: 0.3376697 total: 8.73s remaining: 46.3s
162: learn: 0.3375083 total: 8.79s remaining: 46.2s
163: learn: 0.3373532 total: 8.84s remaining: 46.1s
164: learn: 0.3369999 total: 8.89s remaining: 46.1s
165: learn: 0.3367063 total: 8.95s remaining: 46s
166: learn: 0.3363383 total: 8.99s remaining: 45.9s
167: learn: 0.3361830 total: 9.05s remaining: 45.9s
168: learn: 0.3359305 total: 9.1s remaining: 45.8s
169: learn: 0.3357954 total: 9.15s remaining: 45.8s
170: learn: 0.3356290 total: 9.2s remaining: 45.7s
171: learn: 0.3354718 total: 9.25s remaining: 45.6s
172: learn: 0.3352359 total: 9.3s remaining: 45.5s
173: learn: 0.3349901 total: 9.35s remaining: 45.5s
174: learn: 0.3347143 total: 9.4s remaining: 45.4s
175: learn: 0.3345640 total: 9.45s remaining: 45.3s
176: learn: 0.3343319 total: 9.5s remaining: 45.3s
177: learn: 0.3341281 total: 9.55s remaining: 45.2s
178: learn: 0.3340273 total: 9.6s remaining: 45.1s
179: learn: 0.3340015 total: 9.62s remaining: 44.9s
180: learn: 0.3338943 total: 9.68s remaining: 44.9s
181: learn: 0.3336324 total: 9.73s remaining: 44.8s
182: learn: 0.3331283 total: 9.78s remaining: 44.7s
183: learn: 0.3330400 total: 9.83s remaining: 44.7s
184: learn: 0.3327966 total: 9.88s remaining: 44.6s
185: learn: 0.3324538 total: 9.93s remaining: 44.5s
186: learn: 0.3322629 total: 9.98s remaining: 44.5s
187: learn: 0.3317701 total: 10s remaining: 44.4s
188: learn: 0.3315995 total: 10.1s remaining: 44.3s
189: learn: 0.3313382 total: 10.1s remaining: 44.3s
190: learn: 0.3311131 total: 10.2s remaining: 44.2s
191: learn: 0.3309533 total: 10.2s remaining: 44.2s
192: learn: 0.3307473 total: 10.3s remaining: 44.1s
193: learn: 0.3305694 total: 10.4s remaining: 44.1s
194: learn: 0.3302287 total: 10.4s remaining: 44.1s
195: learn: 0.3301218 total: 10.5s remaining: 44.1s
196: learn: 0.3298699 total: 10.5s remaining: 44.1s
197: learn: 0.3296733 total: 10.6s remaining: 44.1s
198: learn: 0.3295321 total: 10.7s remaining: 44s
199: learn: 0.3293783 total: 10.7s remaining: 44s
200: learn: 0.3292514 total: 10.8s remaining: 44s
201: learn: 0.3291718 total: 10.9s remaining: 44s
202: learn: 0.3289657 total: 10.9s remaining: 44s
203: learn: 0.3288254 total: 11s remaining: 44s
204: learn: 0.3285546 total: 11s remaining: 43.9s
205: learn: 0.3284430 total: 11.1s remaining: 43.9s
206: learn: 0.3282437 total: 11.2s remaining: 43.9s
207: learn: 0.3279990 total: 11.2s remaining: 43.8s
208: learn: 0.3278843 total: 11.3s remaining: 43.8s
209: learn: 0.3277214 total: 11.3s remaining: 43.8s
210: learn: 0.3275542 total: 11.4s remaining: 43.7s
211: learn: 0.3274526 total: 11.5s remaining: 43.7s
212: learn: 0.3272362 total: 11.5s remaining: 43.7s
213: learn: 0.3271557 total: 11.6s remaining: 43.6s
214: learn: 0.3270216 total: 11.6s remaining: 43.6s
215: learn: 0.3269048 total: 11.7s remaining: 43.6s
216: learn: 0.3266966 total: 11.8s remaining: 43.6s
217: learn: 0.3265706 total: 11.8s remaining: 43.5s
218: learn: 0.3263149 total: 11.9s remaining: 43.5s
219: learn: 0.3262435 total: 12s remaining: 43.5s
220: learn: 0.3261473 total: 12s remaining: 43.5s
221: learn: 0.3259821 total: 12.1s remaining: 43.4s
222: learn: 0.3257229 total: 12.1s remaining: 43.4s
223: learn: 0.3256129 total: 12.2s remaining: 43.4s
224: learn: 0.3252286 total: 12.3s remaining: 43.3s
225: learn: 0.3250575 total: 12.3s remaining: 43.3s
226: learn: 0.3248916 total: 12.4s remaining: 43.3s
227: learn: 0.3247729 total: 12.4s remaining: 43.2s
228: learn: 0.3246659 total: 12.5s remaining: 43.2s
229: learn: 0.3243739 total: 12.6s remaining: 43.2s
230: learn: 0.3242068 total: 12.6s remaining: 43.1s
231: learn: 0.3239434 total: 12.7s remaining: 43.1s
232: learn: 0.3237462 total: 12.8s remaining: 43.1s
233: learn: 0.3235852 total: 12.8s remaining: 43.1s
234: learn: 0.3235360 total: 12.9s remaining: 43s
235: learn: 0.3232270 total: 12.9s remaining: 43s
236: learn: 0.3229905 total: 13s remaining: 43s
237: learn: 0.3227229 total: 13.1s remaining: 43s
238: learn: 0.3224642 total: 13.1s remaining: 42.9s
239: learn: 0.3222684 total: 13.2s remaining: 42.9s
240: learn: 0.3221569 total: 13.3s remaining: 42.8s
241: learn: 0.3219216 total: 13.3s remaining: 42.8s
242: learn: 0.3218552 total: 13.4s remaining: 42.8s
243: learn: 0.3215732 total: 13.4s remaining: 42.8s
244: learn: 0.3213776 total: 13.5s remaining: 42.7s
245: learn: 0.3210834 total: 13.6s remaining: 42.7s
246: learn: 0.3209309 total: 13.6s remaining: 42.7s
247: learn: 0.3205368 total: 13.7s remaining: 42.6s
248: learn: 0.3202997 total: 13.7s remaining: 42.5s
249: learn: 0.3201913 total: 13.8s remaining: 42.5s
250: learn: 0.3200838 total: 13.8s remaining: 42.4s
251: learn: 0.3199298 total: 13.9s remaining: 42.3s
252: learn: 0.3197625 total: 13.9s remaining: 42.3s
253: learn: 0.3196524 total: 14s remaining: 42.2s
254: learn: 0.3194423 total: 14s remaining: 42.1s
255: learn: 0.3192714 total: 14.1s remaining: 42s
256: learn: 0.3191143 total: 14.1s remaining: 42s
257: learn: 0.3190127 total: 14.2s remaining: 41.9s
258: learn: 0.3187982 total: 14.2s remaining: 41.8s
259: learn: 0.3186753 total: 14.3s remaining: 41.8s
260: learn: 0.3185564 total: 14.3s remaining: 41.7s
261: learn: 0.3183564 total: 14.4s remaining: 41.6s
262: learn: 0.3181413 total: 14.4s remaining: 41.5s
263: learn: 0.3180100 total: 14.5s remaining: 41.5s
264: learn: 0.3177748 total: 14.5s remaining: 41.4s
265: learn: 0.3175977 total: 14.6s remaining: 41.3s
266: learn: 0.3175402 total: 14.6s remaining: 41.3s
267: learn: 0.3174703 total: 14.7s remaining: 41.2s
268: learn: 0.3172783 total: 14.7s remaining: 41.1s
269: learn: 0.3170599 total: 14.8s remaining: 41.1s
270: learn: 0.3169331 total: 14.8s remaining: 41s
271: learn: 0.3168763 total: 14.9s remaining: 40.9s
272: learn: 0.3167163 total: 14.9s remaining: 40.9s
273: learn: 0.3163747 total: 15s remaining: 40.8s
274: learn: 0.3162784 total: 15s remaining: 40.7s
275: learn: 0.3161827 total: 15.1s remaining: 40.7s
276: learn: 0.3160554 total: 15.1s remaining: 40.6s
277: learn: 0.3159010 total: 15.2s remaining: 40.5s
278: learn: 0.3157180 total: 15.2s remaining: 40.5s
279: learn: 0.3154818 total: 15.3s remaining: 40.4s
280: learn: 0.3153717 total: 15.3s remaining: 40.3s
281: learn: 0.3151801 total: 15.4s remaining: 40.3s
282: learn: 0.3149207 total: 15.4s remaining: 40.2s
283: learn: 0.3148006 total: 15.5s remaining: 40.2s
284: learn: 0.3147244 total: 15.6s remaining: 40.1s
285: learn: 0.3145568 total: 15.6s remaining: 40.1s
286: learn: 0.3143965 total: 15.7s remaining: 40s
287: learn: 0.3143222 total: 15.7s remaining: 39.9s
288: learn: 0.3141228 total: 15.8s remaining: 39.9s
289: learn: 0.3139574 total: 15.8s remaining: 39.8s
290: learn: 0.3138685 total: 15.9s remaining: 39.7s
291: learn: 0.3137517 total: 15.9s remaining: 39.7s
292: learn: 0.3135956 total: 16s remaining: 39.6s
293: learn: 0.3134661 total: 16s remaining: 39.5s
294: learn: 0.3133702 total: 16.1s remaining: 39.5s
295: learn: 0.3130742 total: 16.1s remaining: 39.4s
296: learn: 0.3129110 total: 16.2s remaining: 39.4s
297: learn: 0.3127933 total: 16.2s remaining: 39.3s
298: learn: 0.3126321 total: 16.3s remaining: 39.2s
299: learn: 0.3125761 total: 16.3s remaining: 39.2s
300: learn: 0.3124525 total: 16.4s remaining: 39.1s
301: learn: 0.3123284 total: 16.4s remaining: 39s
302: learn: 0.3122191 total: 16.5s remaining: 39s
303: learn: 0.3120680 total: 16.5s remaining: 38.9s
304: learn: 0.3119421 total: 16.6s remaining: 38.8s
305: learn: 0.3117818 total: 16.6s remaining: 38.8s
306: learn: 0.3116090 total: 16.7s remaining: 38.7s
307: learn: 0.3114060 total: 16.7s remaining: 38.6s
308: learn: 0.3113188 total: 16.8s remaining: 38.6s
309: learn: 0.3111987 total: 16.8s remaining: 38.5s
310: learn: 0.3110237 total: 16.9s remaining: 38.5s
311: learn: 0.3109169 total: 16.9s remaining: 38.4s
312: learn: 0.3107984 total: 17s remaining: 38.3s
313: learn: 0.3106642 total: 17s remaining: 38.3s
314: learn: 0.3105106 total: 17.1s remaining: 38.2s
315: learn: 0.3103455 total: 17.1s remaining: 38.2s
316: learn: 0.3102847 total: 17.2s remaining: 38.1s
317: learn: 0.3101061 total: 17.3s remaining: 38.1s
318: learn: 0.3099832 total: 17.3s remaining: 38.1s
319: learn: 0.3099092 total: 17.4s remaining: 38s
320: learn: 0.3098101 total: 17.4s remaining: 38s
321: learn: 0.3096863 total: 17.6s remaining: 38.1s
322: learn: 0.3096320 total: 17.7s remaining: 38.1s
323: learn: 0.3095068 total: 17.7s remaining: 38.1s
324: learn: 0.3094646 total: 17.8s remaining: 38s
325: learn: 0.3093571 total: 17.8s remaining: 38s
326: learn: 0.3092901 total: 17.9s remaining: 37.9s
327: learn: 0.3091353 total: 18s remaining: 37.9s
328: learn: 0.3090118 total: 18s remaining: 37.9s
329: learn: 0.3088668 total: 18.1s remaining: 37.8s
330: learn: 0.3088055 total: 18.2s remaining: 37.8s
331: learn: 0.3086564 total: 18.2s remaining: 37.7s
332: learn: 0.3083751 total: 18.3s remaining: 37.7s
333: learn: 0.3082397 total: 18.3s remaining: 37.7s
334: learn: 0.3081691 total: 18.4s remaining: 37.6s
335: learn: 0.3080892 total: 18.5s remaining: 37.6s
336: learn: 0.3078747 total: 18.5s remaining: 37.5s
337: learn: 0.3077297 total: 18.6s remaining: 37.5s
338: learn: 0.3076126 total: 18.7s remaining: 37.5s
339: learn: 0.3074138 total: 18.7s remaining: 37.4s
340: learn: 0.3072550 total: 18.8s remaining: 37.4s
341: learn: 0.3071259 total: 18.8s remaining: 37.3s
342: learn: 0.3071248 total: 18.9s remaining: 37.2s
343: learn: 0.3070637 total: 18.9s remaining: 37.2s
344: learn: 0.3069212 total: 19s remaining: 37.1s
345: learn: 0.3067535 total: 19.1s remaining: 37.1s
346: learn: 0.3064203 total: 19.1s remaining: 37.1s
347: learn: 0.3063035 total: 19.2s remaining: 37s
348: learn: 0.3061982 total: 19.2s remaining: 37s
349: learn: 0.3060836 total: 19.3s remaining: 37s
350: learn: 0.3059534 total: 19.4s remaining: 36.9s
351: learn: 0.3057673 total: 19.4s remaining: 36.9s
352: learn: 0.3054897 total: 19.5s remaining: 36.8s
353: learn: 0.3053850 total: 19.5s remaining: 36.8s
354: learn: 0.3051468 total: 19.6s remaining: 36.7s
355: learn: 0.3049381 total: 19.7s remaining: 36.7s
356: learn: 0.3048417 total: 19.7s remaining: 36.7s
357: learn: 0.3047881 total: 19.8s remaining: 36.6s
358: learn: 0.3046783 total: 19.9s remaining: 36.6s
359: learn: 0.3044708 total: 19.9s remaining: 36.5s
360: learn: 0.3043244 total: 20s remaining: 36.5s
361: learn: 0.3041756 total: 20s remaining: 36.4s
362: learn: 0.3040376 total: 20.1s remaining: 36.4s
363: learn: 0.3039540 total: 20.2s remaining: 36.4s
364: learn: 0.3038372 total: 20.2s remaining: 36.3s
365: learn: 0.3038367 total: 20.3s remaining: 36.2s
366: learn: 0.3037363 total: 20.3s remaining: 36.2s
367: learn: 0.3036881 total: 20.4s remaining: 36.1s
368: learn: 0.3035756 total: 20.4s remaining: 36.1s
369: learn: 0.3034993 total: 20.5s remaining: 36s
370: learn: 0.3034583 total: 20.5s remaining: 35.9s
371: learn: 0.3033005 total: 20.6s remaining: 35.9s
372: learn: 0.3031095 total: 20.6s remaining: 35.8s
373: learn: 0.3029441 total: 20.7s remaining: 35.7s
374: learn: 0.3029322 total: 20.7s remaining: 35.7s
375: learn: 0.3028340 total: 20.8s remaining: 35.6s
376: learn: 0.3027373 total: 20.8s remaining: 35.5s
377: learn: 0.3026378 total: 20.9s remaining: 35.5s
378: learn: 0.3025651 total: 20.9s remaining: 35.4s
379: learn: 0.3025648 total: 21s remaining: 35.3s
380: learn: 0.3024876 total: 21s remaining: 35.2s
381: learn: 0.3024048 total: 21.1s remaining: 35.2s
382: learn: 0.3022822 total: 21.1s remaining: 35.1s
383: learn: 0.3021848 total: 21.2s remaining: 35s
384: learn: 0.3020555 total: 21.2s remaining: 35s
385: learn: 0.3019252 total: 21.3s remaining: 34.9s
386: learn: 0.3016979 total: 21.3s remaining: 34.9s
387: learn: 0.3015959 total: 21.4s remaining: 34.8s
388: learn: 0.3014056 total: 21.4s remaining: 34.7s
389: learn: 0.3012207 total: 21.5s remaining: 34.7s
390: learn: 0.3011548 total: 21.5s remaining: 34.6s
391: learn: 0.3009124 total: 21.6s remaining: 34.5s
392: learn: 0.3008587 total: 21.6s remaining: 34.5s
393: learn: 0.3008286 total: 21.7s remaining: 34.4s
394: learn: 0.3007702 total: 21.7s remaining: 34.4s
395: learn: 0.3006222 total: 21.8s remaining: 34.3s
396: learn: 0.3004923 total: 21.8s remaining: 34.2s
397: learn: 0.3004433 total: 21.9s remaining: 34.2s
398: learn: 0.3002063 total: 21.9s remaining: 34.1s
399: learn: 0.3000670 total: 22s remaining: 34s
400: learn: 0.3000175 total: 22s remaining: 34s
401: learn: 0.2998555 total: 22.1s remaining: 33.9s
402: learn: 0.2997486 total: 22.1s remaining: 33.9s
403: learn: 0.2996979 total: 22.2s remaining: 33.8s
404: learn: 0.2995693 total: 22.2s remaining: 33.7s
405: learn: 0.2994502 total: 22.3s remaining: 33.7s
406: learn: 0.2992794 total: 22.3s remaining: 33.6s
407: learn: 0.2991855 total: 22.4s remaining: 33.6s
408: learn: 0.2989987 total: 22.4s remaining: 33.5s
409: learn: 0.2989468 total: 22.5s remaining: 33.4s
410: learn: 0.2988826 total: 22.5s remaining: 33.4s
411: learn: 0.2987430 total: 22.6s remaining: 33.3s
412: learn: 0.2986864 total: 22.6s remaining: 33.2s
413: learn: 0.2985669 total: 22.7s remaining: 33.2s
414: learn: 0.2985406 total: 22.7s remaining: 33.1s
415: learn: 0.2984940 total: 22.8s remaining: 33.1s
416: learn: 0.2983982 total: 22.8s remaining: 33s
417: learn: 0.2983981 total: 22.8s remaining: 32.9s
418: learn: 0.2982805 total: 22.9s remaining: 32.8s
419: learn: 0.2981409 total: 22.9s remaining: 32.8s
420: learn: 0.2979995 total: 23s remaining: 32.7s
421: learn: 0.2979336 total: 23s remaining: 32.7s
422: learn: 0.2977485 total: 23.1s remaining: 32.6s
423: learn: 0.2975669 total: 23.1s remaining: 32.5s
424: learn: 0.2975010 total: 23.2s remaining: 32.5s
425: learn: 0.2973865 total: 23.2s remaining: 32.4s
426: learn: 0.2973410 total: 23.3s remaining: 32.4s
427: learn: 0.2972194 total: 23.4s remaining: 32.3s
428: learn: 0.2971370 total: 23.4s remaining: 32.2s
429: learn: 0.2968372 total: 23.5s remaining: 32.2s
430: learn: 0.2967248 total: 23.5s remaining: 32.1s
431: learn: 0.2965768 total: 23.6s remaining: 32.1s
432: learn: 0.2965488 total: 23.6s remaining: 32s
433: learn: 0.2965373 total: 23.7s remaining: 31.9s
434: learn: 0.2963986 total: 23.7s remaining: 31.9s
435: learn: 0.2961994 total: 23.8s remaining: 31.8s
436: learn: 0.2961477 total: 23.8s remaining: 31.8s
437: learn: 0.2960315 total: 23.9s remaining: 31.7s
438: learn: 0.2960308 total: 23.9s remaining: 31.6s
439: learn: 0.2959134 total: 24s remaining: 31.6s
440: learn: 0.2958742 total: 24s remaining: 31.5s
441: learn: 0.2958037 total: 24.1s remaining: 31.5s
442: learn: 0.2956937 total: 24.1s remaining: 31.4s
443: learn: 0.2956234 total: 24.2s remaining: 31.4s
444: learn: 0.2955329 total: 24.3s remaining: 31.3s
445: learn: 0.2954653 total: 24.3s remaining: 31.3s
446: learn: 0.2953777 total: 24.4s remaining: 31.3s
447: learn: 0.2952535 total: 24.4s remaining: 31.2s
448: learn: 0.2951784 total: 24.5s remaining: 31.2s
449: learn: 0.2950680 total: 24.6s remaining: 31.1s
450: learn: 0.2950329 total: 24.6s remaining: 31.1s
451: learn: 0.2949404 total: 24.7s remaining: 31s
452: learn: 0.2948199 total: 24.7s remaining: 31s
453: learn: 0.2947060 total: 24.8s remaining: 30.9s
454: learn: 0.2946082 total: 24.9s remaining: 30.9s
455: learn: 0.2943881 total: 24.9s remaining: 30.8s
456: learn: 0.2942684 total: 25s remaining: 30.8s
457: learn: 0.2941999 total: 25s remaining: 30.7s
458: learn: 0.2941481 total: 25.1s remaining: 30.7s
459: learn: 0.2939602 total: 25.2s remaining: 30.6s
460: learn: 0.2938671 total: 25.2s remaining: 30.6s
461: learn: 0.2937539 total: 25.3s remaining: 30.5s
462: learn: 0.2936559 total: 25.4s remaining: 30.5s
463: learn: 0.2933926 total: 25.4s remaining: 30.5s
464: learn: 0.2933137 total: 25.5s remaining: 30.4s
465: learn: 0.2931563 total: 25.5s remaining: 30.4s
466: learn: 0.2930391 total: 25.6s remaining: 30.3s
467: learn: 0.2927988 total: 25.7s remaining: 30.3s
468: learn: 0.2926544 total: 25.7s remaining: 30.2s
469: learn: 0.2926080 total: 25.8s remaining: 30.2s
470: learn: 0.2923993 total: 25.9s remaining: 30.1s
471: learn: 0.2922790 total: 25.9s remaining: 30.1s
472: learn: 0.2922006 total: 26s remaining: 30s
473: learn: 0.2920915 total: 26s remaining: 30s
474: learn: 0.2920230 total: 26.1s remaining: 29.9s
475: learn: 0.2919355 total: 26.2s remaining: 29.9s
476: learn: 0.2918100 total: 26.2s remaining: 29.8s
477: learn: 0.2918095 total: 26.2s remaining: 29.8s
478: learn: 0.2916864 total: 26.3s remaining: 29.7s
479: learn: 0.2916140 total: 26.4s remaining: 29.7s
480: learn: 0.2916013 total: 26.4s remaining: 29.6s
481: learn: 0.2914908 total: 26.5s remaining: 29.6s
482: learn: 0.2914323 total: 26.6s remaining: 29.5s
483: learn: 0.2912978 total: 26.6s remaining: 29.5s
484: learn: 0.2912389 total: 26.7s remaining: 29.4s
485: learn: 0.2911239 total: 26.8s remaining: 29.4s
486: learn: 0.2909898 total: 26.8s remaining: 29.4s
487: learn: 0.2909143 total: 26.9s remaining: 29.3s
488: learn: 0.2908265 total: 27s remaining: 29.3s
489: learn: 0.2907320 total: 27s remaining: 29.2s
490: learn: 0.2907089 total: 27.1s remaining: 29.2s
491: learn: 0.2906506 total: 27.1s remaining: 29.1s
492: learn: 0.2905495 total: 27.2s remaining: 29.1s
493: learn: 0.2905264 total: 27.3s remaining: 29s
494: learn: 0.2903259 total: 27.3s remaining: 29s
495: learn: 0.2902481 total: 27.4s remaining: 28.9s
496: learn: 0.2901969 total: 27.4s remaining: 28.8s
497: learn: 0.2901137 total: 27.5s remaining: 28.8s
498: learn: 0.2900215 total: 27.5s remaining: 28.7s
499: learn: 0.2899874 total: 27.6s remaining: 28.7s
500: learn: 0.2899874 total: 27.6s remaining: 28.6s
501: learn: 0.2899869 total: 27.6s remaining: 28.5s
502: learn: 0.2899277 total: 27.7s remaining: 28.4s
503: learn: 0.2899098 total: 27.7s remaining: 28.4s
504: learn: 0.2898358 total: 27.8s remaining: 28.3s
505: learn: 0.2897794 total: 27.8s remaining: 28.3s
506: learn: 0.2896555 total: 27.9s remaining: 28.2s
507: learn: 0.2895679 total: 27.9s remaining: 28.1s
508: learn: 0.2895156 total: 28s remaining: 28.1s
509: learn: 0.2895152 total: 28s remaining: 28s
510: learn: 0.2893047 total: 28s remaining: 27.9s
511: learn: 0.2893044 total: 28.1s remaining: 27.8s
512: learn: 0.2893044 total: 28.1s remaining: 27.7s
513: learn: 0.2892356 total: 28.1s remaining: 27.7s
514: learn: 0.2891083 total: 28.2s remaining: 27.6s
515: learn: 0.2889402 total: 28.2s remaining: 27.6s
516: learn: 0.2888744 total: 28.3s remaining: 27.5s
517: learn: 0.2887787 total: 28.3s remaining: 27.5s
518: learn: 0.2887351 total: 28.4s remaining: 27.4s
519: learn: 0.2886446 total: 28.4s remaining: 27.3s
520: learn: 0.2885126 total: 28.5s remaining: 27.3s
521: learn: 0.2884245 total: 28.6s remaining: 27.3s
522: learn: 0.2884044 total: 28.6s remaining: 27.2s
523: learn: 0.2883601 total: 28.7s remaining: 27.1s
524: learn: 0.2883598 total: 28.7s remaining: 27s
525: learn: 0.2882616 total: 28.7s remaining: 27s
526: learn: 0.2881912 total: 28.8s remaining: 26.9s
527: learn: 0.2880710 total: 28.8s remaining: 26.9s
528: learn: 0.2879431 total: 28.9s remaining: 26.8s
529: learn: 0.2878437 total: 28.9s remaining: 26.8s
530: learn: 0.2876613 total: 29s remaining: 26.7s
531: learn: 0.2876093 total: 29s remaining: 26.6s
532: learn: 0.2876089 total: 29.1s remaining: 26.6s
533: learn: 0.2874741 total: 29.1s remaining: 26.5s
534: learn: 0.2873655 total: 29.2s remaining: 26.4s
535: learn: 0.2872885 total: 29.2s remaining: 26.4s
536: learn: 0.2872700 total: 29.3s remaining: 26.3s
537: learn: 0.2872481 total: 29.3s remaining: 26.3s
538: learn: 0.2871252 total: 29.4s remaining: 26.2s
539: learn: 0.2869622 total: 29.4s remaining: 26.1s
540: learn: 0.2868589 total: 29.5s remaining: 26.1s
541: learn: 0.2868088 total: 29.5s remaining: 26s
542: learn: 0.2866163 total: 29.6s remaining: 26s
543: learn: 0.2864727 total: 29.6s remaining: 25.9s
544: learn: 0.2864460 total: 29.7s remaining: 25.9s
545: learn: 0.2863698 total: 29.7s remaining: 25.8s
546: learn: 0.2862383 total: 29.8s remaining: 25.7s
547: learn: 0.2861715 total: 29.8s remaining: 25.7s
548: learn: 0.2861228 total: 29.9s remaining: 25.6s
549: learn: 0.2860007 total: 29.9s remaining: 25.6s
550: learn: 0.2858266 total: 30s remaining: 25.5s
551: learn: 0.2856992 total: 30s remaining: 25.5s
552: learn: 0.2856932 total: 30.1s remaining: 25.4s
553: learn: 0.2856929 total: 30.1s remaining: 25.3s
554: learn: 0.2855845 total: 30.1s remaining: 25.3s
555: learn: 0.2855492 total: 30.2s remaining: 25.2s
556: learn: 0.2854958 total: 30.3s remaining: 25.1s
557: learn: 0.2853340 total: 30.3s remaining: 25.1s
558: learn: 0.2852264 total: 30.4s remaining: 25s
559: learn: 0.2851754 total: 30.4s remaining: 25s
560: learn: 0.2851494 total: 30.5s remaining: 24.9s
561: learn: 0.2850787 total: 30.5s remaining: 24.9s
562: learn: 0.2849801 total: 30.6s remaining: 24.8s
563: learn: 0.2847239 total: 30.6s remaining: 24.8s
564: learn: 0.2846482 total: 30.7s remaining: 24.7s
565: learn: 0.2846479 total: 30.7s remaining: 24.6s
566: learn: 0.2845668 total: 30.8s remaining: 24.6s
567: learn: 0.2844687 total: 30.8s remaining: 24.5s
568: learn: 0.2842800 total: 30.9s remaining: 24.5s
569: learn: 0.2842127 total: 30.9s remaining: 24.4s
570: learn: 0.2842124 total: 31s remaining: 24.4s
571: learn: 0.2841073 total: 31s remaining: 24.3s
572: learn: 0.2840538 total: 31.1s remaining: 24.3s
573: learn: 0.2839607 total: 31.2s remaining: 24.2s
574: learn: 0.2838073 total: 31.2s remaining: 24.2s
575: learn: 0.2838016 total: 31.3s remaining: 24.1s
576: learn: 0.2837412 total: 31.3s remaining: 24.1s
577: learn: 0.2836790 total: 31.4s remaining: 24s
578: learn: 0.2835284 total: 31.5s remaining: 24s
579: learn: 0.2834181 total: 31.5s remaining: 23.9s
580: learn: 0.2833094 total: 31.6s remaining: 23.9s
581: learn: 0.2831880 total: 31.7s remaining: 23.8s
582: learn: 0.2831388 total: 31.7s remaining: 23.8s
583: learn: 0.2830734 total: 31.8s remaining: 23.7s
584: learn: 0.2829515 total: 31.9s remaining: 23.7s
585: learn: 0.2829118 total: 31.9s remaining: 23.6s
586: learn: 0.2828126 total: 32s remaining: 23.6s
587: learn: 0.2827093 total: 32.1s remaining: 23.5s
588: learn: 0.2826202 total: 32.1s remaining: 23.5s
589: learn: 0.2825922 total: 32.2s remaining: 23.4s
590: learn: 0.2825475 total: 32.2s remaining: 23.4s
591: learn: 0.2825056 total: 32.3s remaining: 23.3s
592: learn: 0.2824342 total: 32.4s remaining: 23.3s
593: learn: 0.2823953 total: 32.4s remaining: 23.2s
594: learn: 0.2823356 total: 32.5s remaining: 23.2s
595: learn: 0.2823082 total: 32.5s remaining: 23.1s
596: learn: 0.2822844 total: 32.6s remaining: 23.1s
597: learn: 0.2821404 total: 32.7s remaining: 23.1s
598: learn: 0.2821156 total: 32.8s remaining: 23s
599: learn: 0.2820437 total: 32.8s remaining: 23s
600: learn: 0.2820422 total: 32.9s remaining: 22.9s
601: learn: 0.2819897 total: 32.9s remaining: 22.9s
602: learn: 0.2819558 total: 33s remaining: 22.8s
603: learn: 0.2819557 total: 33s remaining: 22.7s
604: learn: 0.2819457 total: 33.1s remaining: 22.7s
605: learn: 0.2818335 total: 33.1s remaining: 22.6s
606: learn: 0.2817208 total: 33.2s remaining: 22.6s
607: learn: 0.2817169 total: 33.3s remaining: 22.5s
608: learn: 0.2816635 total: 33.3s remaining: 22.5s
609: learn: 0.2816381 total: 33.4s remaining: 22.4s
610: learn: 0.2815665 total: 33.4s remaining: 22.4s
611: learn: 0.2814356 total: 33.5s remaining: 22.3s
612: learn: 0.2813503 total: 33.6s remaining: 22.3s
613: learn: 0.2812635 total: 33.6s remaining: 22.2s
614: learn: 0.2812167 total: 33.7s remaining: 22.2s
615: learn: 0.2811449 total: 33.8s remaining: 22.1s
616: learn: 0.2810759 total: 33.8s remaining: 22.1s
617: learn: 0.2809883 total: 33.9s remaining: 22s
618: learn: 0.2809392 total: 33.9s remaining: 22s
619: learn: 0.2808297 total: 34s remaining: 21.9s
620: learn: 0.2808078 total: 34.1s remaining: 21.9s
621: learn: 0.2807281 total: 34.1s remaining: 21.8s
622: learn: 0.2806870 total: 34.2s remaining: 21.8s
623: learn: 0.2806512 total: 34.2s remaining: 21.7s
624: learn: 0.2806101 total: 34.3s remaining: 21.7s
625: learn: 0.2805980 total: 34.3s remaining: 21.6s
626: learn: 0.2805628 total: 34.4s remaining: 21.5s
627: learn: 0.2805601 total: 34.4s remaining: 21.5s
628: learn: 0.2805556 total: 34.5s remaining: 21.4s
629: learn: 0.2805135 total: 34.5s remaining: 21.4s
630: learn: 0.2804614 total: 34.6s remaining: 21.3s
631: learn: 0.2803023 total: 34.6s remaining: 21.2s
632: learn: 0.2802051 total: 34.7s remaining: 21.2s
633: learn: 0.2801619 total: 34.7s remaining: 21.1s
634: learn: 0.2801228 total: 34.8s remaining: 21.1s
635: learn: 0.2800505 total: 34.9s remaining: 21.1s
636: learn: 0.2799627 total: 35s remaining: 21s
637: learn: 0.2799082 total: 35s remaining: 21s
638: learn: 0.2798266 total: 35s remaining: 20.9s
639: learn: 0.2798172 total: 35.1s remaining: 20.8s
640: learn: 0.2797892 total: 35.1s remaining: 20.8s
641: learn: 0.2797804 total: 35.2s remaining: 20.7s
642: learn: 0.2797433 total: 35.3s remaining: 20.7s
643: learn: 0.2796471 total: 35.3s remaining: 20.6s
644: learn: 0.2796212 total: 35.4s remaining: 20.6s
645: learn: 0.2796073 total: 35.4s remaining: 20.5s
646: learn: 0.2794054 total: 35.5s remaining: 20.4s
647: learn: 0.2793427 total: 35.5s remaining: 20.4s
648: learn: 0.2793380 total: 35.6s remaining: 20.3s
649: learn: 0.2793337 total: 35.6s remaining: 20.3s
650: learn: 0.2792418 total: 35.7s remaining: 20.2s
651: learn: 0.2791546 total: 35.7s remaining: 20.2s
652: learn: 0.2790822 total: 35.8s remaining: 20.1s
653: learn: 0.2790729 total: 35.8s remaining: 20s
654: learn: 0.2790687 total: 35.9s remaining: 20s
655: learn: 0.2790666 total: 35.9s remaining: 19.9s
656: learn: 0.2789721 total: 36s remaining: 19.9s
657: learn: 0.2789544 total: 36s remaining: 19.8s
658: learn: 0.2788352 total: 36.1s remaining: 19.8s
659: learn: 0.2786334 total: 36.1s remaining: 19.7s
660: learn: 0.2785944 total: 36.2s remaining: 19.6s
661: learn: 0.2785928 total: 36.2s remaining: 19.6s
662: learn: 0.2784918 total: 36.3s remaining: 19.5s
663: learn: 0.2783863 total: 36.3s remaining: 19.5s
664: learn: 0.2782497 total: 36.4s remaining: 19.4s
665: learn: 0.2782389 total: 36.4s remaining: 19.4s
666: learn: 0.2782388 total: 36.4s remaining: 19.3s
667: learn: 0.2782388 total: 36.4s remaining: 19.2s
668: learn: 0.2781276 total: 36.5s remaining: 19.1s
669: learn: 0.2779789 total: 36.5s remaining: 19.1s
670: learn: 0.2779788 total: 36.6s remaining: 19s
671: learn: 0.2779455 total: 36.6s remaining: 19s
672: learn: 0.2778813 total: 36.7s remaining: 18.9s
673: learn: 0.2776370 total: 36.7s remaining: 18.9s
674: learn: 0.2775463 total: 36.8s remaining: 18.8s
675: learn: 0.2775461 total: 36.8s remaining: 18.7s
676: learn: 0.2774805 total: 36.9s remaining: 18.7s
677: learn: 0.2773512 total: 36.9s remaining: 18.6s
678: learn: 0.2773291 total: 37s remaining: 18.6s
679: learn: 0.2772580 total: 37s remaining: 18.5s
680: learn: 0.2772455 total: 37.1s remaining: 18.5s
681: learn: 0.2772063 total: 37.1s remaining: 18.4s
682: learn: 0.2772016 total: 37.2s remaining: 18.3s
683: learn: 0.2771591 total: 37.2s remaining: 18.3s
684: learn: 0.2770791 total: 37.3s remaining: 18.2s
685: learn: 0.2770420 total: 37.3s remaining: 18.2s
686: learn: 0.2770407 total: 37.4s remaining: 18.1s
687: learn: 0.2769424 total: 37.4s remaining: 18.1s
688: learn: 0.2768675 total: 37.5s remaining: 18s
689: learn: 0.2767963 total: 37.5s remaining: 17.9s
690: learn: 0.2767929 total: 37.6s remaining: 17.9s
691: learn: 0.2767479 total: 37.6s remaining: 17.8s
692: learn: 0.2767457 total: 37.7s remaining: 17.8s
693: learn: 0.2766955 total: 37.7s remaining: 17.7s
694: learn: 0.2766345 total: 37.8s remaining: 17.7s
695: learn: 0.2766029 total: 37.9s remaining: 17.6s
696: learn: 0.2766026 total: 37.9s remaining: 17.6s
697: learn: 0.2766012 total: 38s remaining: 17.5s
698: learn: 0.2764918 total: 38s remaining: 17.5s
699: learn: 0.2762661 total: 38.1s remaining: 17.4s
700: learn: 0.2762057 total: 38.2s remaining: 17.4s
701: learn: 0.2762056 total: 38.2s remaining: 17.3s
702: learn: 0.2761672 total: 38.3s remaining: 17.3s
703: learn: 0.2761670 total: 38.3s remaining: 17.2s
704: learn: 0.2761658 total: 38.4s remaining: 17.1s
705: learn: 0.2760129 total: 38.4s remaining: 17.1s
706: learn: 0.2759152 total: 38.5s remaining: 17s
707: learn: 0.2758528 total: 38.5s remaining: 17s
708: learn: 0.2758011 total: 38.6s remaining: 16.9s
709: learn: 0.2757184 total: 38.7s remaining: 16.9s
710: learn: 0.2757131 total: 38.7s remaining: 16.8s
711: learn: 0.2756809 total: 38.8s remaining: 16.8s
712: learn: 0.2756804 total: 38.8s remaining: 16.7s
713: learn: 0.2756186 total: 38.9s remaining: 16.7s
714: learn: 0.2755812 total: 39s remaining: 16.6s
715: learn: 0.2755329 total: 39s remaining: 16.6s
716: learn: 0.2754554 total: 39.1s remaining: 16.5s
717: learn: 0.2754169 total: 39.2s remaining: 16.5s
718: learn: 0.2753973 total: 39.2s remaining: 16.4s
719: learn: 0.2753972 total: 39.3s remaining: 16.4s
720: learn: 0.2753909 total: 39.3s remaining: 16.3s
721: learn: 0.2753442 total: 39.4s remaining: 16.3s
722: learn: 0.2751864 total: 39.5s remaining: 16.2s
723: learn: 0.2751486 total: 39.5s remaining: 16.2s
724: learn: 0.2751408 total: 39.6s remaining: 16.1s
725: learn: 0.2750900 total: 39.6s remaining: 16s
726: learn: 0.2749779 total: 39.7s remaining: 16s
727: learn: 0.2749268 total: 39.8s remaining: 15.9s
728: learn: 0.2748569 total: 39.8s remaining: 15.9s
729: learn: 0.2747444 total: 39.9s remaining: 15.8s
730: learn: 0.2746766 total: 39.9s remaining: 15.8s
731: learn: 0.2746189 total: 40s remaining: 15.7s
732: learn: 0.2745931 total: 40.1s remaining: 15.7s
733: learn: 0.2745165 total: 40.1s remaining: 15.6s
734: learn: 0.2743859 total: 40.2s remaining: 15.6s
735: learn: 0.2742841 total: 40.2s remaining: 15.5s
736: learn: 0.2741745 total: 40.3s remaining: 15.5s
737: learn: 0.2741683 total: 40.4s remaining: 15.4s
738: learn: 0.2741378 total: 40.4s remaining: 15.4s
739: learn: 0.2740855 total: 40.5s remaining: 15.3s
740: learn: 0.2740355 total: 40.5s remaining: 15.3s
741: learn: 0.2739583 total: 40.6s remaining: 15.2s
742: learn: 0.2739580 total: 40.6s remaining: 15.2s
743: learn: 0.2738950 total: 40.7s remaining: 15.1s
744: learn: 0.2737458 total: 40.8s remaining: 15s
745: learn: 0.2736741 total: 40.8s remaining: 15s
746: learn: 0.2736188 total: 40.9s remaining: 14.9s
747: learn: 0.2735993 total: 40.9s remaining: 14.9s
748: learn: 0.2735938 total: 41s remaining: 14.8s
749: learn: 0.2734691 total: 41s remaining: 14.8s
750: learn: 0.2733525 total: 41.1s remaining: 14.7s
751: learn: 0.2733479 total: 41.1s remaining: 14.7s
752: learn: 0.2733472 total: 41.2s remaining: 14.6s
753: learn: 0.2732949 total: 41.2s remaining: 14.5s
754: learn: 0.2732159 total: 41.3s remaining: 14.5s
755: learn: 0.2731479 total: 41.3s remaining: 14.4s
756: learn: 0.2729911 total: 41.4s remaining: 14.4s
757: learn: 0.2728906 total: 41.4s remaining: 14.3s
758: learn: 0.2728621 total: 41.5s remaining: 14.3s
759: learn: 0.2728136 total: 41.5s remaining: 14.2s
760: learn: 0.2727612 total: 41.6s remaining: 14.2s
761: learn: 0.2727029 total: 41.6s remaining: 14.1s
762: learn: 0.2725551 total: 41.7s remaining: 14s
763: learn: 0.2725350 total: 41.7s remaining: 14s
764: learn: 0.2725327 total: 41.8s remaining: 13.9s
765: learn: 0.2723868 total: 41.8s remaining: 13.9s
766: learn: 0.2722326 total: 41.9s remaining: 13.8s
767: learn: 0.2721550 total: 41.9s remaining: 13.8s
768: learn: 0.2720925 total: 42s remaining: 13.7s
769: learn: 0.2720862 total: 42s remaining: 13.6s
770: learn: 0.2720853 total: 42.1s remaining: 13.6s
771: learn: 0.2720581 total: 42.1s remaining: 13.5s
772: learn: 0.2720188 total: 42.2s remaining: 13.5s
773: learn: 0.2719172 total: 42.2s remaining: 13.4s
774: learn: 0.2718988 total: 42.3s remaining: 13.4s
775: learn: 0.2718355 total: 42.3s remaining: 13.3s
776: learn: 0.2716908 total: 42.4s remaining: 13.3s
777: learn: 0.2716169 total: 42.4s remaining: 13.2s
778: learn: 0.2715253 total: 42.5s remaining: 13.1s
779: learn: 0.2714153 total: 42.5s remaining: 13.1s
780: learn: 0.2713227 total: 42.6s remaining: 13s
781: learn: 0.2712829 total: 42.6s remaining: 13s
782: learn: 0.2712825 total: 42.6s remaining: 12.9s
783: learn: 0.2712407 total: 42.7s remaining: 12.9s
784: learn: 0.2711100 total: 42.8s remaining: 12.8s
785: learn: 0.2710088 total: 42.8s remaining: 12.7s
786: learn: 0.2709390 total: 42.9s remaining: 12.7s
787: learn: 0.2709212 total: 42.9s remaining: 12.6s
788: learn: 0.2709200 total: 42.9s remaining: 12.6s
789: learn: 0.2709147 total: 43s remaining: 12.5s
790: learn: 0.2708109 total: 43.1s remaining: 12.5s
791: learn: 0.2707995 total: 43.1s remaining: 12.4s
792: learn: 0.2707599 total: 43.1s remaining: 12.4s
793: learn: 0.2706861 total: 43.2s remaining: 12.3s
794: learn: 0.2706008 total: 43.3s remaining: 12.2s
795: learn: 0.2704774 total: 43.3s remaining: 12.2s
796: learn: 0.2704103 total: 43.4s remaining: 12.1s
797: learn: 0.2704095 total: 43.4s remaining: 12.1s
798: learn: 0.2703989 total: 43.5s remaining: 12s
799: learn: 0.2703034 total: 43.5s remaining: 12s
800: learn: 0.2703019 total: 43.6s remaining: 11.9s
801: learn: 0.2702666 total: 43.6s remaining: 11.9s
802: learn: 0.2702300 total: 43.7s remaining: 11.8s
803: learn: 0.2701439 total: 43.7s remaining: 11.7s
804: learn: 0.2700916 total: 43.8s remaining: 11.7s
805: learn: 0.2699325 total: 43.8s remaining: 11.6s
806: learn: 0.2697616 total: 43.9s remaining: 11.6s
807: learn: 0.2697333 total: 43.9s remaining: 11.5s
808: learn: 0.2696808 total: 44s remaining: 11.5s
809: learn: 0.2696695 total: 44s remaining: 11.4s
810: learn: 0.2696607 total: 44.1s remaining: 11.4s
811: learn: 0.2696282 total: 44.1s remaining: 11.3s
812: learn: 0.2696258 total: 44.2s remaining: 11.2s
813: learn: 0.2696223 total: 44.2s remaining: 11.2s
814: learn: 0.2695394 total: 44.2s remaining: 11.1s
815: learn: 0.2695360 total: 44.3s remaining: 11.1s
816: learn: 0.2695016 total: 44.3s remaining: 11s
817: learn: 0.2694343 total: 44.4s remaining: 11s
818: learn: 0.2693227 total: 44.5s remaining: 10.9s
819: learn: 0.2692858 total: 44.5s remaining: 10.9s
820: learn: 0.2692786 total: 44.6s remaining: 10.8s
821: learn: 0.2692758 total: 44.6s remaining: 10.8s
822: learn: 0.2692758 total: 44.7s remaining: 10.7s
823: learn: 0.2692457 total: 44.7s remaining: 10.6s
824: learn: 0.2692456 total: 44.8s remaining: 10.6s
825: learn: 0.2692103 total: 44.8s remaining: 10.5s
826: learn: 0.2691809 total: 44.9s remaining: 10.5s
827: learn: 0.2690059 total: 44.9s remaining: 10.4s
828: learn: 0.2689986 total: 45s remaining: 10.4s
829: learn: 0.2689239 total: 45.1s remaining: 10.3s
830: learn: 0.2689183 total: 45.1s remaining: 10.3s
831: learn: 0.2689158 total: 45.2s remaining: 10.2s
832: learn: 0.2689025 total: 45.3s remaining: 10.2s
833: learn: 0.2688449 total: 45.3s remaining: 10.1s
834: learn: 0.2688098 total: 45.4s remaining: 10.1s
835: learn: 0.2688098 total: 45.4s remaining: 9.99s
836: learn: 0.2688047 total: 45.5s remaining: 9.94s
837: learn: 0.2688047 total: 45.5s remaining: 9.88s
838: learn: 0.2687639 total: 45.6s remaining: 9.83s
839: learn: 0.2687239 total: 45.6s remaining: 9.78s
840: learn: 0.2687040 total: 45.7s remaining: 9.72s
841: learn: 0.2686003 total: 45.7s remaining: 9.67s
842: learn: 0.2685764 total: 45.8s remaining: 9.62s
843: learn: 0.2685467 total: 45.9s remaining: 9.56s
844: learn: 0.2684202 total: 45.9s remaining: 9.51s
845: learn: 0.2682792 total: 46s remaining: 9.46s
846: learn: 0.2682790 total: 46s remaining: 9.4s
847: learn: 0.2682175 total: 46.1s remaining: 9.35s
848: learn: 0.2682175 total: 46.1s remaining: 9.29s
849: learn: 0.2681579 total: 46.2s remaining: 9.24s
850: learn: 0.2681576 total: 46.2s remaining: 9.18s
851: learn: 0.2681410 total: 46.3s remaining: 9.12s
852: learn: 0.2681405 total: 46.3s remaining: 9.07s
853: learn: 0.2681405 total: 46.4s remaining: 9.01s
854: learn: 0.2681052 total: 46.4s remaining: 8.96s
855: learn: 0.2679178 total: 46.5s remaining: 8.91s
856: learn: 0.2678980 total: 46.6s remaining: 8.86s
857: learn: 0.2678946 total: 46.6s remaining: 8.8s
858: learn: 0.2678164 total: 46.7s remaining: 8.75s
859: learn: 0.2677994 total: 46.7s remaining: 8.7s
860: learn: 0.2677553 total: 46.8s remaining: 8.64s
861: learn: 0.2677452 total: 46.9s remaining: 8.59s
862: learn: 0.2677181 total: 46.9s remaining: 8.54s
863: learn: 0.2676579 total: 47s remaining: 8.48s
864: learn: 0.2675826 total: 47s remaining: 8.43s
865: learn: 0.2673968 total: 47.1s remaining: 8.38s
866: learn: 0.2673306 total: 47.2s remaining: 8.32s
867: learn: 0.2672959 total: 47.2s remaining: 8.27s
868: learn: 0.2672077 total: 47.3s remaining: 8.22s
869: learn: 0.2671486 total: 47.4s remaining: 8.16s
870: learn: 0.2670542 total: 47.4s remaining: 8.11s
871: learn: 0.2669562 total: 47.5s remaining: 8.06s
872: learn: 0.2669562 total: 47.5s remaining: 8s
873: learn: 0.2668965 total: 47.6s remaining: 7.95s
874: learn: 0.2668015 total: 47.6s remaining: 7.89s
875: learn: 0.2667986 total: 47.7s remaining: 7.84s
876: learn: 0.2666717 total: 47.8s remaining: 7.79s
877: learn: 0.2665324 total: 47.8s remaining: 7.73s
878: learn: 0.2664535 total: 47.9s remaining: 7.68s
879: learn: 0.2664452 total: 47.9s remaining: 7.62s
880: learn: 0.2663231 total: 48s remaining: 7.57s
881: learn: 0.2662887 total: 48s remaining: 7.51s
882: learn: 0.2662036 total: 48.1s remaining: 7.46s
883: learn: 0.2662030 total: 48.1s remaining: 7.4s
884: learn: 0.2659060 total: 48.2s remaining: 7.35s
885: learn: 0.2658201 total: 48.2s remaining: 7.29s
886: learn: 0.2657323 total: 48.3s remaining: 7.24s
887: learn: 0.2656619 total: 48.3s remaining: 7.18s
888: learn: 0.2656014 total: 48.4s remaining: 7.13s
889: learn: 0.2654629 total: 48.4s remaining: 7.07s
890: learn: 0.2654279 total: 48.5s remaining: 7.02s
891: learn: 0.2654279 total: 48.5s remaining: 6.96s
892: learn: 0.2653703 total: 48.5s remaining: 6.9s
893: learn: 0.2653217 total: 48.6s remaining: 6.85s
894: learn: 0.2652797 total: 48.6s remaining: 6.79s
895: learn: 0.2652796 total: 48.7s remaining: 6.74s
896: learn: 0.2652676 total: 48.7s remaining: 6.68s
897: learn: 0.2652546 total: 48.8s remaining: 6.63s
898: learn: 0.2651439 total: 48.8s remaining: 6.57s
899: learn: 0.2650567 total: 48.9s remaining: 6.52s
900: learn: 0.2650560 total: 48.9s remaining: 6.46s
901: learn: 0.2650335 total: 49s remaining: 6.41s
902: learn: 0.2648820 total: 49s remaining: 6.35s
903: learn: 0.2648366 total: 49.1s remaining: 6.3s
904: learn: 0.2646525 total: 49.1s remaining: 6.24s
905: learn: 0.2646507 total: 49.2s remaining: 6.19s
906: learn: 0.2645199 total: 49.2s remaining: 6.13s
907: learn: 0.2645030 total: 49.3s remaining: 6.08s
908: learn: 0.2645030 total: 49.3s remaining: 6.02s
909: learn: 0.2643277 total: 49.3s remaining: 5.96s
910: learn: 0.2643179 total: 49.4s remaining: 5.91s
911: learn: 0.2643174 total: 49.4s remaining: 5.85s
912: learn: 0.2642061 total: 49.5s remaining: 5.8s
913: learn: 0.2641595 total: 49.5s remaining: 5.74s
914: learn: 0.2641290 total: 49.6s remaining: 5.69s
915: learn: 0.2641095 total: 49.6s remaining: 5.63s
916: learn: 0.2639977 total: 49.7s remaining: 5.58s
917: learn: 0.2639975 total: 49.7s remaining: 5.52s
918: learn: 0.2639974 total: 49.7s remaining: 5.47s
919: learn: 0.2639271 total: 49.8s remaining: 5.41s
920: learn: 0.2639263 total: 49.8s remaining: 5.36s
921: learn: 0.2638266 total: 49.9s remaining: 5.3s
922: learn: 0.2637822 total: 49.9s remaining: 5.25s
923: learn: 0.2637722 total: 50s remaining: 5.19s
924: learn: 0.2637722 total: 50s remaining: 5.14s
925: learn: 0.2637716 total: 50.1s remaining: 5.08s
926: learn: 0.2637715 total: 50.1s remaining: 5.03s
927: learn: 0.2637715 total: 50.1s remaining: 4.97s
928: learn: 0.2637713 total: 50.2s remaining: 4.91s
929: learn: 0.2637231 total: 50.2s remaining: 4.86s
930: learn: 0.2636553 total: 50.3s remaining: 4.81s
931: learn: 0.2636553 total: 50.3s remaining: 4.75s
932: learn: 0.2636552 total: 50.3s remaining: 4.69s
933: learn: 0.2636509 total: 50.4s remaining: 4.64s
934: learn: 0.2636031 total: 50.4s remaining: 4.58s
935: learn: 0.2633734 total: 50.5s remaining: 4.53s
936: learn: 0.2633732 total: 50.5s remaining: 4.47s
937: learn: 0.2633714 total: 50.6s remaining: 4.42s
938: learn: 0.2633365 total: 50.6s remaining: 4.37s
939: learn: 0.2632732 total: 50.7s remaining: 4.31s
940: learn: 0.2632729 total: 50.7s remaining: 4.26s
941: learn: 0.2632348 total: 50.8s remaining: 4.2s
942: learn: 0.2631898 total: 50.8s remaining: 4.15s
943: learn: 0.2631774 total: 50.9s remaining: 4.09s
944: learn: 0.2631667 total: 50.9s remaining: 4.04s
945: learn: 0.2631494 total: 51s remaining: 3.99s
946: learn: 0.2630918 total: 51s remaining: 3.93s
947: learn: 0.2630917 total: 51s remaining: 3.88s
948: learn: 0.2630768 total: 51.1s remaining: 3.82s
949: learn: 0.2630236 total: 51.1s remaining: 3.77s
950: learn: 0.2629854 total: 51.2s remaining: 3.71s
951: learn: 0.2629674 total: 51.2s remaining: 3.66s
952: learn: 0.2629673 total: 51.3s remaining: 3.6s
953: learn: 0.2629625 total: 51.3s remaining: 3.55s
954: learn: 0.2629511 total: 51.4s remaining: 3.5s
955: learn: 0.2629387 total: 51.5s remaining: 3.44s
956: learn: 0.2629365 total: 51.5s remaining: 3.39s
957: learn: 0.2628519 total: 51.6s remaining: 3.34s
958: learn: 0.2628486 total: 51.6s remaining: 3.28s
959: learn: 0.2628014 total: 51.7s remaining: 3.23s
960: learn: 0.2627931 total: 51.8s remaining: 3.18s
961: learn: 0.2626666 total: 51.8s remaining: 3.12s
962: learn: 0.2626379 total: 51.9s remaining: 3.07s
963: learn: 0.2626258 total: 51.9s remaining: 3.02s
964: learn: 0.2626164 total: 52s remaining: 2.96s
965: learn: 0.2624708 total: 52.1s remaining: 2.91s
966: learn: 0.2624433 total: 52.1s remaining: 2.86s
967: learn: 0.2623957 total: 52.2s remaining: 2.8s
968: learn: 0.2623379 total: 52.2s remaining: 2.75s
969: learn: 0.2623310 total: 52.3s remaining: 2.7s
970: learn: 0.2622618 total: 52.4s remaining: 2.64s
971: learn: 0.2622093 total: 52.4s remaining: 2.59s
972: learn: 0.2621375 total: 52.5s remaining: 2.54s
973: learn: 0.2620966 total: 52.6s remaining: 2.48s
974: learn: 0.2620607 total: 52.6s remaining: 2.43s
975: learn: 0.2620353 total: 52.7s remaining: 2.37s
976: learn: 0.2619821 total: 52.7s remaining: 2.32s
977: learn: 0.2619716 total: 52.8s remaining: 2.27s
978: learn: 0.2619232 total: 52.9s remaining: 2.21s
979: learn: 0.2618400 total: 52.9s remaining: 2.16s
980: learn: 0.2618098 total: 53s remaining: 2.11s
981: learn: 0.2617592 total: 53s remaining: 2.05s
982: learn: 0.2617496 total: 53.1s remaining: 2s
983: learn: 0.2616566 total: 53.2s remaining: 1.94s
984: learn: 0.2615916 total: 53.2s remaining: 1.89s
985: learn: 0.2614431 total: 53.3s remaining: 1.84s
986: learn: 0.2614153 total: 53.3s remaining: 1.78s
987: learn: 0.2612854 total: 53.4s remaining: 1.73s
988: learn: 0.2612568 total: 53.5s remaining: 1.68s
989: learn: 0.2612467 total: 53.5s remaining: 1.62s
990: learn: 0.2611679 total: 53.6s remaining: 1.57s
991: learn: 0.2611518 total: 53.7s remaining: 1.51s
992: learn: 0.2611431 total: 53.7s remaining: 1.46s
993: learn: 0.2611113 total: 53.8s remaining: 1.41s
994: learn: 0.2610792 total: 53.8s remaining: 1.35s
995: learn: 0.2610448 total: 53.9s remaining: 1.3s
996: learn: 0.2610403 total: 54s remaining: 1.24s
997: learn: 0.2610258 total: 54s remaining: 1.19s
998: learn: 0.2610002 total: 54.1s remaining: 1.14s
999: learn: 0.2609436 total: 54.1s remaining: 1.08s
1000: learn: 0.2609279 total: 54.2s remaining: 1.03s
1001: learn: 0.2609230 total: 54.3s remaining: 975ms
1002: learn: 0.2608832 total: 54.3s remaining: 921ms
1003: learn: 0.2608515 total: 54.4s remaining: 867ms
1004: learn: 0.2607976 total: 54.5s remaining: 813ms
1005: learn: 0.2607614 total: 54.5s remaining: 759ms
1006: learn: 0.2607062 total: 54.6s remaining: 705ms
1007: learn: 0.2606853 total: 54.6s remaining: 650ms
1008: learn: 0.2606685 total: 54.7s remaining: 596ms
1009: learn: 0.2606338 total: 54.7s remaining: 542ms
1010: learn: 0.2606337 total: 54.8s remaining: 488ms
1011: learn: 0.2605958 total: 54.8s remaining: 433ms
1012: learn: 0.2605943 total: 54.9s remaining: 379ms
1013: learn: 0.2605864 total: 54.9s remaining: 325ms
1014: learn: 0.2605464 total: 55s remaining: 271ms
1015: learn: 0.2605442 total: 55s remaining: 216ms
1016: learn: 0.2605005 total: 55s remaining: 162ms
1017: learn: 0.2602531 total: 55.1s remaining: 108ms
1018: learn: 0.2601655 total: 55.2s remaining: 54.1ms
1019: learn: 0.2601193 total: 55.2s remaining: 0us
Finished training fold 4 - running score 0.8630581621767414
Running fold 5, 15737 train samples, 2622 validation samples
0: learn: 0.6482718 total: 53.9ms remaining: 54.9s
1: learn: 0.6095071 total: 109ms remaining: 55.5s
2: learn: 0.5761305 total: 166ms remaining: 56.3s
3: learn: 0.5471595 total: 220ms remaining: 55.9s
4: learn: 0.5224634 total: 273ms remaining: 55.3s
5: learn: 0.5013810 total: 324ms remaining: 54.7s
6: learn: 0.4829338 total: 374ms remaining: 54.1s
7: learn: 0.4671801 total: 426ms remaining: 53.9s
8: learn: 0.4535366 total: 476ms remaining: 53.5s
9: learn: 0.4417253 total: 525ms remaining: 53s
10: learn: 0.4314851 total: 575ms remaining: 52.7s
11: learn: 0.4225836 total: 624ms remaining: 52.4s
12: learn: 0.4148885 total: 677ms remaining: 52.5s
13: learn: 0.4082950 total: 728ms remaining: 52.3s
14: learn: 0.4025720 total: 777ms remaining: 52.1s
15: learn: 0.3976583 total: 828ms remaining: 51.9s
16: learn: 0.3932661 total: 878ms remaining: 51.8s
17: learn: 0.3897956 total: 899ms remaining: 50s
18: learn: 0.3862738 total: 951ms remaining: 50.1s
19: learn: 0.3833274 total: 1s remaining: 50s
20: learn: 0.3808110 total: 1.08s remaining: 51.4s
21: learn: 0.3785041 total: 1.13s remaining: 51.4s
22: learn: 0.3766426 total: 1.18s remaining: 50.9s
23: learn: 0.3749569 total: 1.21s remaining: 50.4s
24: learn: 0.3734036 total: 1.26s remaining: 50.4s
25: learn: 0.3720166 total: 1.31s remaining: 50.3s
26: learn: 0.3706459 total: 1.37s remaining: 50.3s
27: learn: 0.3694991 total: 1.42s remaining: 50.2s
28: learn: 0.3686256 total: 1.46s remaining: 50.1s
29: learn: 0.3678244 total: 1.51s remaining: 50s
30: learn: 0.3671890 total: 1.54s remaining: 49.1s
31: learn: 0.3666219 total: 1.57s remaining: 48.5s
32: learn: 0.3660234 total: 1.62s remaining: 48.5s
33: learn: 0.3653987 total: 1.67s remaining: 48.4s
34: learn: 0.3648574 total: 1.72s remaining: 48.4s
35: learn: 0.3644026 total: 1.77s remaining: 48.5s
36: learn: 0.3638442 total: 1.82s remaining: 48.4s
37: learn: 0.3633020 total: 1.87s remaining: 48.3s
38: learn: 0.3629040 total: 1.92s remaining: 48.3s
39: learn: 0.3625465 total: 1.97s remaining: 48.3s
40: learn: 0.3622300 total: 2.02s remaining: 48.2s
41: learn: 0.3620512 total: 2.04s remaining: 47.5s
42: learn: 0.3616375 total: 2.12s remaining: 48.1s
43: learn: 0.3612778 total: 2.16s remaining: 48s
44: learn: 0.3610443 total: 2.22s remaining: 48s
45: learn: 0.3606780 total: 2.27s remaining: 48s
46: learn: 0.3605070 total: 2.32s remaining: 48s
47: learn: 0.3602092 total: 2.37s remaining: 47.9s
48: learn: 0.3597648 total: 2.42s remaining: 47.9s
49: learn: 0.3595281 total: 2.47s remaining: 47.9s
50: learn: 0.3591734 total: 2.52s remaining: 47.9s
51: learn: 0.3589516 total: 2.57s remaining: 47.8s
52: learn: 0.3587098 total: 2.62s remaining: 47.7s
53: learn: 0.3584304 total: 2.67s remaining: 47.7s
54: learn: 0.3581817 total: 2.72s remaining: 47.7s
55: learn: 0.3579744 total: 2.77s remaining: 47.7s
56: learn: 0.3578197 total: 2.83s remaining: 47.8s
57: learn: 0.3574245 total: 2.89s remaining: 48s
58: learn: 0.3572077 total: 2.95s remaining: 48.1s
59: learn: 0.3570406 total: 3s remaining: 48s
60: learn: 0.3568131 total: 3.06s remaining: 48.1s
61: learn: 0.3565100 total: 3.12s remaining: 48.2s
62: learn: 0.3563047 total: 3.18s remaining: 48.3s
63: learn: 0.3558453 total: 3.25s remaining: 48.5s
64: learn: 0.3556267 total: 3.31s remaining: 48.6s
65: learn: 0.3552331 total: 3.37s remaining: 48.7s
66: learn: 0.3548600 total: 3.43s remaining: 48.8s
67: learn: 0.3546272 total: 3.49s remaining: 48.9s
68: learn: 0.3544254 total: 3.55s remaining: 49s
69: learn: 0.3542559 total: 3.61s remaining: 49s
70: learn: 0.3540911 total: 3.67s remaining: 49s
71: learn: 0.3539115 total: 3.73s remaining: 49.1s
72: learn: 0.3537616 total: 3.79s remaining: 49.2s
73: learn: 0.3534799 total: 3.85s remaining: 49.3s
74: learn: 0.3533523 total: 3.92s remaining: 49.4s
75: learn: 0.3533207 total: 3.96s remaining: 49.2s
76: learn: 0.3530497 total: 4.02s remaining: 49.2s
77: learn: 0.3528867 total: 4.08s remaining: 49.2s
78: learn: 0.3526464 total: 4.14s remaining: 49.3s
79: learn: 0.3523024 total: 4.2s remaining: 49.3s
80: learn: 0.3520932 total: 4.26s remaining: 49.4s
81: learn: 0.3518235 total: 4.32s remaining: 49.5s
82: learn: 0.3517020 total: 4.38s remaining: 49.5s
83: learn: 0.3514687 total: 4.44s remaining: 49.5s
84: learn: 0.3511931 total: 4.5s remaining: 49.6s
85: learn: 0.3510250 total: 4.56s remaining: 49.6s
86: learn: 0.3507756 total: 4.63s remaining: 49.6s
87: learn: 0.3505162 total: 4.68s remaining: 49.6s
88: learn: 0.3503946 total: 4.74s remaining: 49.6s
89: learn: 0.3501693 total: 4.81s remaining: 49.7s
90: learn: 0.3499842 total: 4.87s remaining: 49.7s
91: learn: 0.3498130 total: 4.93s remaining: 49.7s
92: learn: 0.3495329 total: 4.99s remaining: 49.8s
93: learn: 0.3493187 total: 5.05s remaining: 49.8s
94: learn: 0.3489844 total: 5.11s remaining: 49.8s
95: learn: 0.3488061 total: 5.17s remaining: 49.8s
96: learn: 0.3485906 total: 5.24s remaining: 49.8s
97: learn: 0.3483458 total: 5.3s remaining: 49.8s
98: learn: 0.3481099 total: 5.37s remaining: 49.9s
99: learn: 0.3480098 total: 5.43s remaining: 49.9s
100: learn: 0.3476484 total: 5.49s remaining: 49.9s
101: learn: 0.3474417 total: 5.55s remaining: 49.9s
102: learn: 0.3473242 total: 5.61s remaining: 49.9s
103: learn: 0.3471314 total: 5.67s remaining: 49.9s
104: learn: 0.3469026 total: 5.73s remaining: 49.9s
105: learn: 0.3465731 total: 5.79s remaining: 50s
106: learn: 0.3463834 total: 5.85s remaining: 50s
107: learn: 0.3462124 total: 5.92s remaining: 50s
108: learn: 0.3460080 total: 5.98s remaining: 50s
109: learn: 0.3458385 total: 6.04s remaining: 50s
110: learn: 0.3454786 total: 6.11s remaining: 50s
111: learn: 0.3452577 total: 6.17s remaining: 50s
112: learn: 0.3451146 total: 6.23s remaining: 50s
113: learn: 0.3448495 total: 6.28s remaining: 49.9s
114: learn: 0.3446748 total: 6.33s remaining: 49.8s
115: learn: 0.3445903 total: 6.38s remaining: 49.7s
116: learn: 0.3444780 total: 6.43s remaining: 49.6s
117: learn: 0.3444778 total: 6.45s remaining: 49.3s
118: learn: 0.3442628 total: 6.5s remaining: 49.2s
119: learn: 0.3441081 total: 6.55s remaining: 49.1s
120: learn: 0.3437260 total: 6.6s remaining: 49.1s
121: learn: 0.3433824 total: 6.66s remaining: 49s
122: learn: 0.3432426 total: 6.71s remaining: 48.9s
123: learn: 0.3430520 total: 6.76s remaining: 48.8s
124: learn: 0.3428553 total: 6.8s remaining: 48.7s
125: learn: 0.3426682 total: 6.85s remaining: 48.6s
126: learn: 0.3425578 total: 6.91s remaining: 48.6s
127: learn: 0.3424594 total: 6.95s remaining: 48.5s
128: learn: 0.3420363 total: 7s remaining: 48.4s
129: learn: 0.3418863 total: 7.06s remaining: 48.3s
130: learn: 0.3416729 total: 7.11s remaining: 48.2s
131: learn: 0.3414443 total: 7.16s remaining: 48.2s
132: learn: 0.3412686 total: 7.21s remaining: 48.1s
133: learn: 0.3411514 total: 7.26s remaining: 48s
134: learn: 0.3409896 total: 7.31s remaining: 47.9s
135: learn: 0.3408884 total: 7.37s remaining: 47.9s
136: learn: 0.3406528 total: 7.42s remaining: 47.8s
137: learn: 0.3405253 total: 7.47s remaining: 47.7s
138: learn: 0.3404013 total: 7.52s remaining: 47.7s
139: learn: 0.3399545 total: 7.57s remaining: 47.6s
140: learn: 0.3398481 total: 7.62s remaining: 47.5s
141: learn: 0.3396733 total: 7.67s remaining: 47.4s
142: learn: 0.3394389 total: 7.72s remaining: 47.3s
143: learn: 0.3392760 total: 7.77s remaining: 47.3s
144: learn: 0.3391016 total: 7.82s remaining: 47.2s
145: learn: 0.3389362 total: 7.87s remaining: 47.1s
146: learn: 0.3386436 total: 7.92s remaining: 47s
147: learn: 0.3385101 total: 7.97s remaining: 46.9s
148: learn: 0.3383451 total: 8.02s remaining: 46.9s
149: learn: 0.3380400 total: 8.07s remaining: 46.8s
150: learn: 0.3377415 total: 8.12s remaining: 46.7s
151: learn: 0.3376129 total: 8.18s remaining: 46.7s
152: learn: 0.3374775 total: 8.22s remaining: 46.6s
153: learn: 0.3373225 total: 8.27s remaining: 46.5s
154: learn: 0.3372495 total: 8.32s remaining: 46.4s
155: learn: 0.3370354 total: 8.37s remaining: 46.4s
156: learn: 0.3368430 total: 8.42s remaining: 46.3s
157: learn: 0.3365160 total: 8.47s remaining: 46.2s
158: learn: 0.3363116 total: 8.52s remaining: 46.2s
159: learn: 0.3360203 total: 8.57s remaining: 46.1s
160: learn: 0.3357807 total: 8.62s remaining: 46s
161: learn: 0.3355712 total: 8.67s remaining: 45.9s
162: learn: 0.3353883 total: 8.72s remaining: 45.8s
163: learn: 0.3351829 total: 8.77s remaining: 45.8s
164: learn: 0.3349277 total: 8.82s remaining: 45.7s
165: learn: 0.3347263 total: 8.87s remaining: 45.6s
166: learn: 0.3344761 total: 8.92s remaining: 45.5s
167: learn: 0.3343261 total: 8.96s remaining: 45.5s
168: learn: 0.3341149 total: 9.02s remaining: 45.4s
169: learn: 0.3339270 total: 9.07s remaining: 45.3s
170: learn: 0.3338455 total: 9.12s remaining: 45.3s
171: learn: 0.3336361 total: 9.17s remaining: 45.2s
172: learn: 0.3334744 total: 9.22s remaining: 45.2s
173: learn: 0.3332848 total: 9.28s remaining: 45.1s
174: learn: 0.3330180 total: 9.32s remaining: 45s
175: learn: 0.3327522 total: 9.37s remaining: 45s
176: learn: 0.3325605 total: 9.43s remaining: 44.9s
177: learn: 0.3323508 total: 9.48s remaining: 44.8s
178: learn: 0.3321230 total: 9.53s remaining: 44.8s
179: learn: 0.3318284 total: 9.58s remaining: 44.7s
180: learn: 0.3315761 total: 9.63s remaining: 44.6s
181: learn: 0.3313817 total: 9.69s remaining: 44.6s
182: learn: 0.3310451 total: 9.75s remaining: 44.6s
183: learn: 0.3308177 total: 9.8s remaining: 44.5s
184: learn: 0.3304538 total: 9.87s remaining: 44.5s
185: learn: 0.3302689 total: 9.93s remaining: 44.5s
186: learn: 0.3299829 total: 9.99s remaining: 44.5s
187: learn: 0.3298460 total: 10s remaining: 44.5s
188: learn: 0.3296431 total: 10.1s remaining: 44.5s
189: learn: 0.3293717 total: 10.2s remaining: 44.4s
190: learn: 0.3292182 total: 10.2s remaining: 44.4s
191: learn: 0.3290862 total: 10.3s remaining: 44.4s
192: learn: 0.3289661 total: 10.4s remaining: 44.4s
193: learn: 0.3287953 total: 10.4s remaining: 44.3s
194: learn: 0.3285586 total: 10.5s remaining: 44.3s
195: learn: 0.3284406 total: 10.5s remaining: 44.3s
196: learn: 0.3281984 total: 10.6s remaining: 44.3s
197: learn: 0.3280434 total: 10.7s remaining: 44.2s
198: learn: 0.3278548 total: 10.7s remaining: 44.2s
199: learn: 0.3276728 total: 10.8s remaining: 44.2s
200: learn: 0.3275526 total: 10.8s remaining: 44.2s
201: learn: 0.3273983 total: 10.9s remaining: 44.2s
202: learn: 0.3272364 total: 11s remaining: 44.1s
203: learn: 0.3270117 total: 11s remaining: 44.1s
204: learn: 0.3268295 total: 11.1s remaining: 44.1s
205: learn: 0.3265951 total: 11.1s remaining: 44s
206: learn: 0.3263834 total: 11.2s remaining: 44s
207: learn: 0.3261283 total: 11.3s remaining: 44s
208: learn: 0.3260009 total: 11.3s remaining: 43.9s
209: learn: 0.3257481 total: 11.4s remaining: 43.9s
210: learn: 0.3255957 total: 11.5s remaining: 43.9s
211: learn: 0.3254242 total: 11.5s remaining: 43.9s
212: learn: 0.3252348 total: 11.6s remaining: 43.8s
213: learn: 0.3250615 total: 11.6s remaining: 43.8s
214: learn: 0.3249180 total: 11.7s remaining: 43.8s
215: learn: 0.3247807 total: 11.8s remaining: 43.8s
216: learn: 0.3245588 total: 11.8s remaining: 43.7s
217: learn: 0.3242278 total: 11.9s remaining: 43.7s
218: learn: 0.3240651 total: 11.9s remaining: 43.7s
219: learn: 0.3237144 total: 12s remaining: 43.7s
220: learn: 0.3235595 total: 12.1s remaining: 43.6s
221: learn: 0.3234312 total: 12.1s remaining: 43.6s
222: learn: 0.3232833 total: 12.2s remaining: 43.6s
223: learn: 0.3231024 total: 12.3s remaining: 43.5s
224: learn: 0.3229969 total: 12.3s remaining: 43.5s
225: learn: 0.3228208 total: 12.4s remaining: 43.5s
226: learn: 0.3227095 total: 12.4s remaining: 43.5s
227: learn: 0.3225268 total: 12.5s remaining: 43.4s
228: learn: 0.3223714 total: 12.6s remaining: 43.4s
229: learn: 0.3222234 total: 12.6s remaining: 43.4s
230: learn: 0.3221274 total: 12.7s remaining: 43.4s
231: learn: 0.3219070 total: 12.8s remaining: 43.3s
232: learn: 0.3215743 total: 12.8s remaining: 43.3s
233: learn: 0.3213477 total: 12.9s remaining: 43.3s
234: learn: 0.3212254 total: 12.9s remaining: 43.2s
235: learn: 0.3209931 total: 13s remaining: 43.2s
236: learn: 0.3207000 total: 13.1s remaining: 43.2s
237: learn: 0.3205541 total: 13.1s remaining: 43.1s
238: learn: 0.3204855 total: 13.2s remaining: 43s
239: learn: 0.3202765 total: 13.2s remaining: 43s
240: learn: 0.3200776 total: 13.3s remaining: 42.9s
241: learn: 0.3198005 total: 13.3s remaining: 42.8s
242: learn: 0.3195236 total: 13.4s remaining: 42.8s
243: learn: 0.3194387 total: 13.4s remaining: 42.7s
244: learn: 0.3193239 total: 13.5s remaining: 42.6s
245: learn: 0.3190824 total: 13.5s remaining: 42.6s
246: learn: 0.3189518 total: 13.6s remaining: 42.5s
247: learn: 0.3187947 total: 13.6s remaining: 42.4s
248: learn: 0.3186217 total: 13.7s remaining: 42.4s
249: learn: 0.3184946 total: 13.7s remaining: 42.3s
250: learn: 0.3183246 total: 13.8s remaining: 42.2s
251: learn: 0.3182241 total: 13.8s remaining: 42.2s
252: learn: 0.3179282 total: 13.9s remaining: 42.1s
253: learn: 0.3177417 total: 13.9s remaining: 42s
254: learn: 0.3174531 total: 14s remaining: 42s
255: learn: 0.3174074 total: 14s remaining: 41.9s
256: learn: 0.3173258 total: 14.1s remaining: 41.8s
257: learn: 0.3171694 total: 14.1s remaining: 41.7s
258: learn: 0.3168919 total: 14.2s remaining: 41.7s
259: learn: 0.3166720 total: 14.2s remaining: 41.6s
260: learn: 0.3165513 total: 14.3s remaining: 41.5s
261: learn: 0.3164145 total: 14.3s remaining: 41.5s
262: learn: 0.3162336 total: 14.4s remaining: 41.4s
263: learn: 0.3160565 total: 14.4s remaining: 41.3s
264: learn: 0.3157954 total: 14.5s remaining: 41.3s
265: learn: 0.3156665 total: 14.5s remaining: 41.2s
266: learn: 0.3154316 total: 14.6s remaining: 41.2s
267: learn: 0.3152750 total: 14.6s remaining: 41.1s
268: learn: 0.3151360 total: 14.7s remaining: 41s
269: learn: 0.3149210 total: 14.7s remaining: 41s
270: learn: 0.3147781 total: 14.8s remaining: 40.9s
271: learn: 0.3145977 total: 14.8s remaining: 40.8s
272: learn: 0.3145312 total: 14.9s remaining: 40.8s
273: learn: 0.3143361 total: 14.9s remaining: 40.7s
274: learn: 0.3140773 total: 15s remaining: 40.6s
275: learn: 0.3138061 total: 15s remaining: 40.6s
276: learn: 0.3136861 total: 15.1s remaining: 40.5s
277: learn: 0.3132898 total: 15.1s remaining: 40.4s
278: learn: 0.3130590 total: 15.2s remaining: 40.4s
279: learn: 0.3128737 total: 15.2s remaining: 40.3s
280: learn: 0.3125520 total: 15.3s remaining: 40.2s
281: learn: 0.3124339 total: 15.3s remaining: 40.2s
282: learn: 0.3122444 total: 15.4s remaining: 40.1s
283: learn: 0.3121316 total: 15.4s remaining: 40s
284: learn: 0.3119045 total: 15.5s remaining: 40s
285: learn: 0.3118914 total: 15.5s remaining: 39.9s
286: learn: 0.3117818 total: 15.6s remaining: 39.8s
287: learn: 0.3117094 total: 15.7s remaining: 39.8s
288: learn: 0.3116109 total: 15.7s remaining: 39.7s
289: learn: 0.3116103 total: 15.7s remaining: 39.6s
290: learn: 0.3114803 total: 15.8s remaining: 39.5s
291: learn: 0.3113073 total: 15.8s remaining: 39.5s
292: learn: 0.3111664 total: 15.9s remaining: 39.4s
293: learn: 0.3111141 total: 15.9s remaining: 39.3s
294: learn: 0.3110244 total: 16s remaining: 39.3s
295: learn: 0.3109107 total: 16s remaining: 39.2s
296: learn: 0.3107374 total: 16.1s remaining: 39.1s
297: learn: 0.3106344 total: 16.1s remaining: 39.1s
298: learn: 0.3105399 total: 16.2s remaining: 39s
299: learn: 0.3103727 total: 16.2s remaining: 39s
300: learn: 0.3101973 total: 16.3s remaining: 38.9s
301: learn: 0.3100519 total: 16.3s remaining: 38.8s
302: learn: 0.3097962 total: 16.4s remaining: 38.8s
303: learn: 0.3095339 total: 16.4s remaining: 38.7s
304: learn: 0.3094575 total: 16.5s remaining: 38.6s
305: learn: 0.3093944 total: 16.5s remaining: 38.6s
306: learn: 0.3091779 total: 16.6s remaining: 38.5s
307: learn: 0.3090713 total: 16.7s remaining: 38.5s
308: learn: 0.3089081 total: 16.7s remaining: 38.5s
309: learn: 0.3087526 total: 16.8s remaining: 38.4s
310: learn: 0.3086238 total: 16.8s remaining: 38.4s
311: learn: 0.3085069 total: 16.9s remaining: 38.4s
312: learn: 0.3084043 total: 17s remaining: 38.3s
313: learn: 0.3081256 total: 17s remaining: 38.3s
314: learn: 0.3079874 total: 17.1s remaining: 38.2s
315: learn: 0.3078293 total: 17.1s remaining: 38.2s
316: learn: 0.3076862 total: 17.2s remaining: 38.1s
317: learn: 0.3075440 total: 17.3s remaining: 38.1s
318: learn: 0.3074542 total: 17.3s remaining: 38.1s
319: learn: 0.3072935 total: 17.4s remaining: 38s
320: learn: 0.3072833 total: 17.4s remaining: 38s
321: learn: 0.3072831 total: 17.5s remaining: 37.9s
322: learn: 0.3071812 total: 17.5s remaining: 37.8s
323: learn: 0.3069310 total: 17.6s remaining: 37.8s
324: learn: 0.3068487 total: 17.6s remaining: 37.7s
325: learn: 0.3068445 total: 17.7s remaining: 37.6s
326: learn: 0.3067782 total: 17.7s remaining: 37.6s
327: learn: 0.3067306 total: 17.8s remaining: 37.6s
328: learn: 0.3065901 total: 17.9s remaining: 37.5s
329: learn: 0.3064729 total: 17.9s remaining: 37.5s
330: learn: 0.3062510 total: 18s remaining: 37.4s
331: learn: 0.3060215 total: 18s remaining: 37.4s
332: learn: 0.3058532 total: 18.1s remaining: 37.3s
333: learn: 0.3057632 total: 18.2s remaining: 37.3s
334: learn: 0.3056818 total: 18.2s remaining: 37.3s
335: learn: 0.3056816 total: 18.2s remaining: 37.1s
336: learn: 0.3055340 total: 18.3s remaining: 37.1s
337: learn: 0.3053519 total: 18.4s remaining: 37.1s
338: learn: 0.3052706 total: 18.4s remaining: 37s
339: learn: 0.3051858 total: 18.5s remaining: 37s
340: learn: 0.3051856 total: 18.5s remaining: 36.8s
341: learn: 0.3049755 total: 18.6s remaining: 36.8s
342: learn: 0.3047658 total: 18.6s remaining: 36.8s
343: learn: 0.3046156 total: 18.7s remaining: 36.7s
344: learn: 0.3045220 total: 18.8s remaining: 36.7s
345: learn: 0.3044583 total: 18.8s remaining: 36.6s
346: learn: 0.3044013 total: 18.9s remaining: 36.6s
347: learn: 0.3043143 total: 18.9s remaining: 36.6s
348: learn: 0.3042285 total: 19s remaining: 36.5s
349: learn: 0.3041881 total: 19.1s remaining: 36.5s
350: learn: 0.3041152 total: 19.1s remaining: 36.4s
351: learn: 0.3039541 total: 19.2s remaining: 36.4s
352: learn: 0.3038738 total: 19.2s remaining: 36.4s
353: learn: 0.3038110 total: 19.3s remaining: 36.3s
354: learn: 0.3037976 total: 19.4s remaining: 36.3s
355: learn: 0.3036378 total: 19.4s remaining: 36.2s
356: learn: 0.3034756 total: 19.5s remaining: 36.2s
357: learn: 0.3034125 total: 19.5s remaining: 36.1s
358: learn: 0.3033277 total: 19.6s remaining: 36.1s
359: learn: 0.3031563 total: 19.7s remaining: 36s
360: learn: 0.3030257 total: 19.7s remaining: 36s
361: learn: 0.3029345 total: 19.8s remaining: 36s
362: learn: 0.3028440 total: 19.8s remaining: 35.9s
363: learn: 0.3027175 total: 19.9s remaining: 35.9s
364: learn: 0.3026942 total: 20s remaining: 35.8s
365: learn: 0.3025976 total: 20s remaining: 35.8s
366: learn: 0.3025018 total: 20.1s remaining: 35.7s
367: learn: 0.3024040 total: 20.1s remaining: 35.7s
368: learn: 0.3023673 total: 20.2s remaining: 35.6s
369: learn: 0.3022973 total: 20.2s remaining: 35.5s
370: learn: 0.3022173 total: 20.3s remaining: 35.5s
371: learn: 0.3021160 total: 20.3s remaining: 35.4s
372: learn: 0.3020276 total: 20.4s remaining: 35.3s
373: learn: 0.3017822 total: 20.4s remaining: 35.3s
374: learn: 0.3016116 total: 20.5s remaining: 35.2s
375: learn: 0.3014510 total: 20.5s remaining: 35.2s
376: learn: 0.3013517 total: 20.6s remaining: 35.1s
377: learn: 0.3012619 total: 20.6s remaining: 35s
378: learn: 0.3011674 total: 20.7s remaining: 35s
379: learn: 0.3011498 total: 20.7s remaining: 34.9s
380: learn: 0.3008822 total: 20.8s remaining: 34.8s
381: learn: 0.3007755 total: 20.8s remaining: 34.8s
382: learn: 0.3006867 total: 20.9s remaining: 34.7s
383: learn: 0.3004295 total: 20.9s remaining: 34.7s
384: learn: 0.3002913 total: 21s remaining: 34.6s
385: learn: 0.3001499 total: 21s remaining: 34.5s
386: learn: 0.3000403 total: 21.1s remaining: 34.5s
387: learn: 0.2999782 total: 21.1s remaining: 34.4s
388: learn: 0.2998951 total: 21.2s remaining: 34.3s
389: learn: 0.2997900 total: 21.2s remaining: 34.3s
390: learn: 0.2997312 total: 21.3s remaining: 34.2s
391: learn: 0.2995315 total: 21.3s remaining: 34.2s
392: learn: 0.2994068 total: 21.4s remaining: 34.1s
393: learn: 0.2992192 total: 21.4s remaining: 34.1s
394: learn: 0.2989902 total: 21.5s remaining: 34s
395: learn: 0.2989393 total: 21.5s remaining: 34s
396: learn: 0.2987789 total: 21.6s remaining: 33.9s
397: learn: 0.2987537 total: 21.6s remaining: 33.8s
398: learn: 0.2986703 total: 21.7s remaining: 33.8s
399: learn: 0.2985658 total: 21.7s remaining: 33.7s
400: learn: 0.2984788 total: 21.8s remaining: 33.6s
401: learn: 0.2984289 total: 21.8s remaining: 33.6s
402: learn: 0.2982562 total: 21.9s remaining: 33.5s
403: learn: 0.2981767 total: 21.9s remaining: 33.5s
404: learn: 0.2980464 total: 22s remaining: 33.4s
405: learn: 0.2978849 total: 22.1s remaining: 33.4s
406: learn: 0.2977668 total: 22.1s remaining: 33.3s
407: learn: 0.2976206 total: 22.2s remaining: 33.2s
408: learn: 0.2975594 total: 22.2s remaining: 33.2s
409: learn: 0.2974506 total: 22.3s remaining: 33.1s
410: learn: 0.2973300 total: 22.3s remaining: 33.1s
411: learn: 0.2972894 total: 22.4s remaining: 33s
412: learn: 0.2972081 total: 22.4s remaining: 32.9s
413: learn: 0.2971590 total: 22.5s remaining: 32.9s
414: learn: 0.2970340 total: 22.5s remaining: 32.8s
415: learn: 0.2970195 total: 22.6s remaining: 32.8s
416: learn: 0.2969029 total: 22.6s remaining: 32.7s
417: learn: 0.2968643 total: 22.7s remaining: 32.6s
418: learn: 0.2967614 total: 22.7s remaining: 32.6s
419: learn: 0.2966955 total: 22.8s remaining: 32.5s
420: learn: 0.2966954 total: 22.8s remaining: 32.4s
421: learn: 0.2966376 total: 22.8s remaining: 32.4s
422: learn: 0.2964885 total: 22.9s remaining: 32.3s
423: learn: 0.2964636 total: 22.9s remaining: 32.2s
424: learn: 0.2963265 total: 23s remaining: 32.2s
425: learn: 0.2963168 total: 23s remaining: 32.1s
426: learn: 0.2962701 total: 23.1s remaining: 32.1s
427: learn: 0.2961206 total: 23.1s remaining: 32s
428: learn: 0.2960280 total: 23.2s remaining: 31.9s
429: learn: 0.2960098 total: 23.2s remaining: 31.9s
430: learn: 0.2959127 total: 23.3s remaining: 31.8s
431: learn: 0.2956914 total: 23.3s remaining: 31.8s
432: learn: 0.2955000 total: 23.4s remaining: 31.7s
433: learn: 0.2954998 total: 23.4s remaining: 31.6s
434: learn: 0.2953350 total: 23.5s remaining: 31.6s
435: learn: 0.2952856 total: 23.5s remaining: 31.5s
436: learn: 0.2950481 total: 23.6s remaining: 31.5s
437: learn: 0.2948641 total: 23.7s remaining: 31.4s
438: learn: 0.2947768 total: 23.7s remaining: 31.4s
439: learn: 0.2947337 total: 23.8s remaining: 31.4s
440: learn: 0.2947335 total: 23.8s remaining: 31.3s
441: learn: 0.2946576 total: 23.9s remaining: 31.2s
442: learn: 0.2944940 total: 23.9s remaining: 31.2s
443: learn: 0.2943748 total: 24s remaining: 31.1s
444: learn: 0.2942916 total: 24.1s remaining: 31.1s
445: learn: 0.2940543 total: 24.1s remaining: 31.1s
446: learn: 0.2939641 total: 24.2s remaining: 31s
447: learn: 0.2939640 total: 24.2s remaining: 30.9s
448: learn: 0.2938555 total: 24.3s remaining: 30.9s
449: learn: 0.2938094 total: 24.3s remaining: 30.8s
450: learn: 0.2937439 total: 24.4s remaining: 30.8s
451: learn: 0.2935594 total: 24.5s remaining: 30.7s
452: learn: 0.2934808 total: 24.5s remaining: 30.7s
453: learn: 0.2933748 total: 24.6s remaining: 30.6s
454: learn: 0.2933155 total: 24.6s remaining: 30.6s
455: learn: 0.2930919 total: 24.7s remaining: 30.6s
456: learn: 0.2930688 total: 24.8s remaining: 30.5s
457: learn: 0.2930687 total: 24.8s remaining: 30.4s
458: learn: 0.2929800 total: 24.8s remaining: 30.4s
459: learn: 0.2928308 total: 24.9s remaining: 30.3s
460: learn: 0.2926088 total: 25s remaining: 30.3s
461: learn: 0.2925299 total: 25s remaining: 30.2s
462: learn: 0.2924737 total: 25.1s remaining: 30.2s
463: learn: 0.2923829 total: 25.2s remaining: 30.1s
464: learn: 0.2923356 total: 25.2s remaining: 30.1s
465: learn: 0.2922809 total: 25.3s remaining: 30s
466: learn: 0.2922442 total: 25.3s remaining: 30s
467: learn: 0.2921134 total: 25.4s remaining: 30s
468: learn: 0.2919696 total: 25.5s remaining: 29.9s
469: learn: 0.2917798 total: 25.5s remaining: 29.9s
470: learn: 0.2916264 total: 25.6s remaining: 29.8s
471: learn: 0.2915325 total: 25.6s remaining: 29.8s
472: learn: 0.2913645 total: 25.7s remaining: 29.7s
473: learn: 0.2913427 total: 25.8s remaining: 29.7s
474: learn: 0.2911994 total: 25.8s remaining: 29.6s
475: learn: 0.2909259 total: 25.9s remaining: 29.6s
476: learn: 0.2907077 total: 25.9s remaining: 29.5s
477: learn: 0.2906400 total: 26s remaining: 29.5s
478: learn: 0.2905587 total: 26.1s remaining: 29.4s
479: learn: 0.2905140 total: 26.1s remaining: 29.4s
480: learn: 0.2904201 total: 26.2s remaining: 29.3s
481: learn: 0.2903652 total: 26.2s remaining: 29.3s
482: learn: 0.2902238 total: 26.3s remaining: 29.2s
483: learn: 0.2901494 total: 26.4s remaining: 29.2s
484: learn: 0.2898377 total: 26.4s remaining: 29.2s
485: learn: 0.2897458 total: 26.5s remaining: 29.1s
486: learn: 0.2896071 total: 26.5s remaining: 29.1s
487: learn: 0.2894822 total: 26.6s remaining: 29s
488: learn: 0.2893872 total: 26.7s remaining: 29s
489: learn: 0.2892854 total: 26.7s remaining: 28.9s
490: learn: 0.2892846 total: 26.8s remaining: 28.8s
491: learn: 0.2892315 total: 26.8s remaining: 28.8s
492: learn: 0.2891043 total: 26.9s remaining: 28.7s
493: learn: 0.2891033 total: 26.9s remaining: 28.6s
494: learn: 0.2889667 total: 26.9s remaining: 28.6s
495: learn: 0.2888659 total: 27s remaining: 28.5s
496: learn: 0.2887891 total: 27s remaining: 28.5s
497: learn: 0.2886488 total: 27.1s remaining: 28.4s
498: learn: 0.2886471 total: 27.1s remaining: 28.3s
499: learn: 0.2885464 total: 27.2s remaining: 28.3s
500: learn: 0.2884938 total: 27.2s remaining: 28.2s
501: learn: 0.2884896 total: 27.3s remaining: 28.1s
502: learn: 0.2883396 total: 27.3s remaining: 28.1s
503: learn: 0.2879814 total: 27.4s remaining: 28s
504: learn: 0.2877767 total: 27.4s remaining: 28s
505: learn: 0.2877042 total: 27.5s remaining: 27.9s
506: learn: 0.2876082 total: 27.5s remaining: 27.9s
507: learn: 0.2875716 total: 27.6s remaining: 27.8s
508: learn: 0.2875401 total: 27.6s remaining: 27.7s
509: learn: 0.2874618 total: 27.7s remaining: 27.7s
510: learn: 0.2873373 total: 27.7s remaining: 27.6s
511: learn: 0.2871806 total: 27.8s remaining: 27.6s
512: learn: 0.2869078 total: 27.9s remaining: 27.5s
513: learn: 0.2867264 total: 27.9s remaining: 27.5s
514: learn: 0.2866003 total: 27.9s remaining: 27.4s
515: learn: 0.2865369 total: 28s remaining: 27.3s
516: learn: 0.2862717 total: 28s remaining: 27.3s
517: learn: 0.2862661 total: 28.1s remaining: 27.2s
518: learn: 0.2862161 total: 28.1s remaining: 27.2s
519: learn: 0.2861493 total: 28.2s remaining: 27.1s
520: learn: 0.2860695 total: 28.2s remaining: 27.1s
521: learn: 0.2860694 total: 28.3s remaining: 27s
522: learn: 0.2860502 total: 28.3s remaining: 26.9s
523: learn: 0.2860223 total: 28.4s remaining: 26.8s
524: learn: 0.2859691 total: 28.4s remaining: 26.8s
525: learn: 0.2858587 total: 28.5s remaining: 26.7s
526: learn: 0.2857445 total: 28.5s remaining: 26.7s
527: learn: 0.2855414 total: 28.6s remaining: 26.6s
528: learn: 0.2854669 total: 28.6s remaining: 26.6s
529: learn: 0.2854149 total: 28.7s remaining: 26.5s
530: learn: 0.2853636 total: 28.7s remaining: 26.5s
531: learn: 0.2853195 total: 28.8s remaining: 26.4s
532: learn: 0.2852215 total: 28.9s remaining: 26.4s
533: learn: 0.2852214 total: 28.9s remaining: 26.3s
534: learn: 0.2852213 total: 28.9s remaining: 26.2s
535: learn: 0.2850030 total: 29s remaining: 26.1s
536: learn: 0.2849426 total: 29s remaining: 26.1s
537: learn: 0.2848168 total: 29.1s remaining: 26s
538: learn: 0.2848092 total: 29.1s remaining: 26s
539: learn: 0.2847698 total: 29.2s remaining: 25.9s
540: learn: 0.2846622 total: 29.2s remaining: 25.9s
541: learn: 0.2845683 total: 29.3s remaining: 25.8s
542: learn: 0.2845454 total: 29.4s remaining: 25.8s
543: learn: 0.2844094 total: 29.4s remaining: 25.7s
544: learn: 0.2843555 total: 29.5s remaining: 25.7s
545: learn: 0.2842437 total: 29.5s remaining: 25.6s
546: learn: 0.2841325 total: 29.6s remaining: 25.6s
547: learn: 0.2840109 total: 29.6s remaining: 25.5s
548: learn: 0.2839323 total: 29.7s remaining: 25.5s
549: learn: 0.2837816 total: 29.7s remaining: 25.4s
550: learn: 0.2836309 total: 29.8s remaining: 25.3s
551: learn: 0.2836308 total: 29.8s remaining: 25.3s
552: learn: 0.2835725 total: 29.9s remaining: 25.2s
553: learn: 0.2834483 total: 29.9s remaining: 25.2s
554: learn: 0.2833556 total: 30s remaining: 25.1s
555: learn: 0.2832285 total: 30s remaining: 25.1s
556: learn: 0.2832019 total: 30.1s remaining: 25s
557: learn: 0.2831230 total: 30.1s remaining: 25s
558: learn: 0.2830738 total: 30.2s remaining: 24.9s
559: learn: 0.2830457 total: 30.3s remaining: 24.9s
560: learn: 0.2828378 total: 30.3s remaining: 24.8s
561: learn: 0.2826631 total: 30.4s remaining: 24.8s
562: learn: 0.2824635 total: 30.5s remaining: 24.7s
563: learn: 0.2823707 total: 30.5s remaining: 24.7s
564: learn: 0.2823705 total: 30.6s remaining: 24.6s
565: learn: 0.2823139 total: 30.6s remaining: 24.6s
566: learn: 0.2822684 total: 30.7s remaining: 24.5s
567: learn: 0.2822002 total: 30.8s remaining: 24.5s
568: learn: 0.2821177 total: 30.8s remaining: 24.4s
569: learn: 0.2819913 total: 30.9s remaining: 24.4s
570: learn: 0.2819912 total: 30.9s remaining: 24.3s
571: learn: 0.2818185 total: 31s remaining: 24.3s
572: learn: 0.2817562 total: 31.1s remaining: 24.2s
573: learn: 0.2817562 total: 31.1s remaining: 24.1s
574: learn: 0.2816429 total: 31.1s remaining: 24.1s
575: learn: 0.2814942 total: 31.2s remaining: 24.1s
576: learn: 0.2813612 total: 31.3s remaining: 24s
577: learn: 0.2813489 total: 31.3s remaining: 24s
578: learn: 0.2813455 total: 31.4s remaining: 23.9s
579: learn: 0.2812687 total: 31.5s remaining: 23.9s
580: learn: 0.2811707 total: 31.6s remaining: 23.8s
581: learn: 0.2809924 total: 31.6s remaining: 23.8s
582: learn: 0.2809375 total: 31.7s remaining: 23.8s
583: learn: 0.2808884 total: 31.8s remaining: 23.7s
584: learn: 0.2808883 total: 31.8s remaining: 23.7s
585: learn: 0.2808249 total: 31.9s remaining: 23.6s
586: learn: 0.2807923 total: 31.9s remaining: 23.6s
587: learn: 0.2807536 total: 32s remaining: 23.5s
588: learn: 0.2806061 total: 32.1s remaining: 23.5s
589: learn: 0.2805328 total: 32.1s remaining: 23.4s
590: learn: 0.2804445 total: 32.2s remaining: 23.4s
591: learn: 0.2803800 total: 32.3s remaining: 23.3s
592: learn: 0.2802154 total: 32.3s remaining: 23.3s
593: learn: 0.2800436 total: 32.4s remaining: 23.2s
594: learn: 0.2799799 total: 32.5s remaining: 23.2s
595: learn: 0.2798474 total: 32.5s remaining: 23.2s
596: learn: 0.2797928 total: 32.6s remaining: 23.1s
597: learn: 0.2796524 total: 32.7s remaining: 23.1s
598: learn: 0.2795154 total: 32.8s remaining: 23s
599: learn: 0.2794748 total: 32.8s remaining: 23s
600: learn: 0.2794236 total: 32.9s remaining: 22.9s
601: learn: 0.2792602 total: 32.9s remaining: 22.9s
602: learn: 0.2791191 total: 33s remaining: 22.8s
603: learn: 0.2790712 total: 33.1s remaining: 22.8s
604: learn: 0.2789663 total: 33.2s remaining: 22.7s
605: learn: 0.2789480 total: 33.2s remaining: 22.7s
606: learn: 0.2788786 total: 33.3s remaining: 22.6s
607: learn: 0.2788289 total: 33.3s remaining: 22.6s
608: learn: 0.2787701 total: 33.4s remaining: 22.5s
609: learn: 0.2787243 total: 33.5s remaining: 22.5s
610: learn: 0.2786944 total: 33.5s remaining: 22.4s
611: learn: 0.2786685 total: 33.6s remaining: 22.4s
612: learn: 0.2786634 total: 33.7s remaining: 22.4s
613: learn: 0.2784929 total: 33.7s remaining: 22.3s
614: learn: 0.2784527 total: 33.8s remaining: 22.2s
615: learn: 0.2783793 total: 33.8s remaining: 22.2s
616: learn: 0.2782895 total: 33.9s remaining: 22.1s
617: learn: 0.2782156 total: 34s remaining: 22.1s
618: learn: 0.2781527 total: 34s remaining: 22s
619: learn: 0.2779481 total: 34.1s remaining: 22s
620: learn: 0.2778384 total: 34.1s remaining: 21.9s
621: learn: 0.2777914 total: 34.2s remaining: 21.9s
622: learn: 0.2776481 total: 34.2s remaining: 21.8s
623: learn: 0.2775044 total: 34.3s remaining: 21.8s
624: learn: 0.2773526 total: 34.3s remaining: 21.7s
625: learn: 0.2773110 total: 34.4s remaining: 21.6s
626: learn: 0.2771156 total: 34.4s remaining: 21.6s
627: learn: 0.2769634 total: 34.5s remaining: 21.5s
628: learn: 0.2769248 total: 34.6s remaining: 21.5s
629: learn: 0.2767609 total: 34.6s remaining: 21.4s
630: learn: 0.2766469 total: 34.7s remaining: 21.4s
631: learn: 0.2764234 total: 34.7s remaining: 21.3s
632: learn: 0.2763402 total: 34.8s remaining: 21.3s
633: learn: 0.2762574 total: 34.8s remaining: 21.2s
634: learn: 0.2761337 total: 34.9s remaining: 21.2s
635: learn: 0.2759482 total: 34.9s remaining: 21.1s
636: learn: 0.2757898 total: 35s remaining: 21s
637: learn: 0.2757408 total: 35s remaining: 21s
638: learn: 0.2756726 total: 35.1s remaining: 20.9s
639: learn: 0.2756173 total: 35.2s remaining: 20.9s
640: learn: 0.2755483 total: 35.2s remaining: 20.8s
641: learn: 0.2753439 total: 35.3s remaining: 20.8s
642: learn: 0.2752126 total: 35.3s remaining: 20.7s
643: learn: 0.2751617 total: 35.4s remaining: 20.7s
644: learn: 0.2751137 total: 35.4s remaining: 20.6s
645: learn: 0.2749651 total: 35.5s remaining: 20.5s
646: learn: 0.2749404 total: 35.5s remaining: 20.5s
647: learn: 0.2748866 total: 35.6s remaining: 20.4s
648: learn: 0.2747856 total: 35.7s remaining: 20.4s
649: learn: 0.2746896 total: 35.7s remaining: 20.3s
650: learn: 0.2744427 total: 35.8s remaining: 20.3s
651: learn: 0.2743595 total: 35.8s remaining: 20.2s
652: learn: 0.2742895 total: 35.9s remaining: 20.2s
653: learn: 0.2742459 total: 35.9s remaining: 20.1s
654: learn: 0.2741966 total: 36s remaining: 20s
655: learn: 0.2740773 total: 36s remaining: 20s
656: learn: 0.2740268 total: 36.1s remaining: 19.9s
657: learn: 0.2740019 total: 36.1s remaining: 19.9s
658: learn: 0.2739144 total: 36.2s remaining: 19.8s
659: learn: 0.2737063 total: 36.2s remaining: 19.8s
660: learn: 0.2735011 total: 36.3s remaining: 19.7s
661: learn: 0.2734277 total: 36.3s remaining: 19.7s
662: learn: 0.2732879 total: 36.4s remaining: 19.6s
663: learn: 0.2732848 total: 36.4s remaining: 19.5s
664: learn: 0.2732097 total: 36.5s remaining: 19.5s
665: learn: 0.2731162 total: 36.5s remaining: 19.4s
666: learn: 0.2730454 total: 36.6s remaining: 19.4s
667: learn: 0.2729729 total: 36.6s remaining: 19.3s
668: learn: 0.2728887 total: 36.7s remaining: 19.3s
669: learn: 0.2728628 total: 36.8s remaining: 19.2s
670: learn: 0.2728173 total: 36.8s remaining: 19.1s
671: learn: 0.2727170 total: 36.9s remaining: 19.1s
672: learn: 0.2725693 total: 36.9s remaining: 19s
673: learn: 0.2723807 total: 37s remaining: 19s
674: learn: 0.2722646 total: 37s remaining: 18.9s
675: learn: 0.2722008 total: 37.1s remaining: 18.9s
676: learn: 0.2721232 total: 37.2s remaining: 18.8s
677: learn: 0.2720795 total: 37.2s remaining: 18.8s
678: learn: 0.2720767 total: 37.3s remaining: 18.7s
679: learn: 0.2719988 total: 37.4s remaining: 18.7s
680: learn: 0.2718869 total: 37.4s remaining: 18.6s
681: learn: 0.2717257 total: 37.5s remaining: 18.6s
682: learn: 0.2715684 total: 37.6s remaining: 18.5s
683: learn: 0.2715536 total: 37.6s remaining: 18.5s
684: learn: 0.2714818 total: 37.7s remaining: 18.4s
685: learn: 0.2714608 total: 37.8s remaining: 18.4s
686: learn: 0.2714575 total: 37.8s remaining: 18.3s
687: learn: 0.2713072 total: 37.9s remaining: 18.3s
688: learn: 0.2712726 total: 37.9s remaining: 18.2s
689: learn: 0.2711499 total: 38s remaining: 18.2s
690: learn: 0.2710415 total: 38.1s remaining: 18.1s
691: learn: 0.2710383 total: 38.1s remaining: 18.1s
692: learn: 0.2710245 total: 38.2s remaining: 18s
693: learn: 0.2709233 total: 38.3s remaining: 18s
694: learn: 0.2707896 total: 38.3s remaining: 17.9s
695: learn: 0.2707269 total: 38.4s remaining: 17.9s
696: learn: 0.2705825 total: 38.5s remaining: 17.8s
697: learn: 0.2705697 total: 38.5s remaining: 17.8s
698: learn: 0.2705073 total: 38.6s remaining: 17.7s
699: learn: 0.2705065 total: 38.7s remaining: 17.7s
700: learn: 0.2698999 total: 38.7s remaining: 17.6s
701: learn: 0.2697827 total: 38.8s remaining: 17.6s
702: learn: 0.2695864 total: 38.8s remaining: 17.5s
703: learn: 0.2693666 total: 38.9s remaining: 17.5s
704: learn: 0.2693032 total: 39s remaining: 17.4s
705: learn: 0.2692481 total: 39s remaining: 17.4s
706: learn: 0.2692024 total: 39.1s remaining: 17.3s
707: learn: 0.2691988 total: 39.2s remaining: 17.3s
708: learn: 0.2691268 total: 39.2s remaining: 17.2s
709: learn: 0.2690664 total: 39.3s remaining: 17.2s
710: learn: 0.2690602 total: 39.4s remaining: 17.1s
711: learn: 0.2690219 total: 39.4s remaining: 17s
712: learn: 0.2690016 total: 39.5s remaining: 17s
713: learn: 0.2690015 total: 39.5s remaining: 16.9s
714: learn: 0.2690014 total: 39.5s remaining: 16.9s
715: learn: 0.2689998 total: 39.6s remaining: 16.8s
716: learn: 0.2689160 total: 39.6s remaining: 16.8s
717: learn: 0.2688433 total: 39.7s remaining: 16.7s
718: learn: 0.2688430 total: 39.7s remaining: 16.6s
719: learn: 0.2688018 total: 39.8s remaining: 16.6s
720: learn: 0.2686993 total: 39.9s remaining: 16.5s
721: learn: 0.2686970 total: 39.9s remaining: 16.5s
722: learn: 0.2686477 total: 40s remaining: 16.4s
723: learn: 0.2685380 total: 40s remaining: 16.4s
724: learn: 0.2685217 total: 40.1s remaining: 16.3s
725: learn: 0.2684457 total: 40.2s remaining: 16.3s
726: learn: 0.2683972 total: 40.2s remaining: 16.2s
727: learn: 0.2683799 total: 40.3s remaining: 16.2s
728: learn: 0.2682810 total: 40.4s remaining: 16.1s
729: learn: 0.2682394 total: 40.4s remaining: 16.1s
730: learn: 0.2681606 total: 40.5s remaining: 16s
731: learn: 0.2680242 total: 40.6s remaining: 16s
732: learn: 0.2679428 total: 40.6s remaining: 15.9s
733: learn: 0.2678901 total: 40.7s remaining: 15.8s
734: learn: 0.2678239 total: 40.7s remaining: 15.8s
735: learn: 0.2675991 total: 40.8s remaining: 15.7s
736: learn: 0.2675938 total: 40.8s remaining: 15.7s
737: learn: 0.2675134 total: 40.9s remaining: 15.6s
738: learn: 0.2674387 total: 40.9s remaining: 15.6s
739: learn: 0.2673308 total: 41s remaining: 15.5s
740: learn: 0.2672556 total: 41.1s remaining: 15.5s
741: learn: 0.2670760 total: 41.1s remaining: 15.4s
742: learn: 0.2670546 total: 41.2s remaining: 15.3s
743: learn: 0.2670477 total: 41.2s remaining: 15.3s
744: learn: 0.2670461 total: 41.3s remaining: 15.2s
745: learn: 0.2670394 total: 41.3s remaining: 15.2s
746: learn: 0.2670361 total: 41.4s remaining: 15.1s
747: learn: 0.2669582 total: 41.4s remaining: 15.1s
748: learn: 0.2669487 total: 41.5s remaining: 15s
749: learn: 0.2669255 total: 41.5s remaining: 14.9s
750: learn: 0.2668194 total: 41.6s remaining: 14.9s
751: learn: 0.2667161 total: 41.6s remaining: 14.8s
752: learn: 0.2666039 total: 41.7s remaining: 14.8s
753: learn: 0.2666015 total: 41.7s remaining: 14.7s
754: learn: 0.2664970 total: 41.8s remaining: 14.7s
755: learn: 0.2663991 total: 41.8s remaining: 14.6s
756: learn: 0.2662041 total: 41.9s remaining: 14.6s
757: learn: 0.2661601 total: 41.9s remaining: 14.5s
758: learn: 0.2660587 total: 42s remaining: 14.4s
759: learn: 0.2660569 total: 42s remaining: 14.4s
760: learn: 0.2660324 total: 42.1s remaining: 14.3s
761: learn: 0.2659162 total: 42.1s remaining: 14.3s
762: learn: 0.2658569 total: 42.2s remaining: 14.2s
763: learn: 0.2657278 total: 42.3s remaining: 14.2s
764: learn: 0.2657148 total: 42.3s remaining: 14.1s
765: learn: 0.2656364 total: 42.4s remaining: 14s
766: learn: 0.2655409 total: 42.4s remaining: 14s
767: learn: 0.2654627 total: 42.5s remaining: 13.9s
768: learn: 0.2654061 total: 42.5s remaining: 13.9s
769: learn: 0.2653452 total: 42.6s remaining: 13.8s
770: learn: 0.2652942 total: 42.6s remaining: 13.8s
771: learn: 0.2652383 total: 42.7s remaining: 13.7s
772: learn: 0.2651706 total: 42.7s remaining: 13.7s
773: learn: 0.2650118 total: 42.8s remaining: 13.6s
774: learn: 0.2649362 total: 42.9s remaining: 13.5s
775: learn: 0.2649329 total: 42.9s remaining: 13.5s
776: learn: 0.2648110 total: 43s remaining: 13.4s
777: learn: 0.2647972 total: 43s remaining: 13.4s
778: learn: 0.2647141 total: 43.1s remaining: 13.3s
779: learn: 0.2647102 total: 43.1s remaining: 13.3s
780: learn: 0.2644487 total: 43.2s remaining: 13.2s
781: learn: 0.2644098 total: 43.2s remaining: 13.2s
782: learn: 0.2643421 total: 43.3s remaining: 13.1s
783: learn: 0.2643125 total: 43.3s remaining: 13s
784: learn: 0.2642970 total: 43.4s remaining: 13s
785: learn: 0.2642691 total: 43.4s remaining: 12.9s
786: learn: 0.2642659 total: 43.5s remaining: 12.9s
787: learn: 0.2641477 total: 43.5s remaining: 12.8s
788: learn: 0.2640597 total: 43.6s remaining: 12.8s
789: learn: 0.2639935 total: 43.6s remaining: 12.7s
790: learn: 0.2639095 total: 43.7s remaining: 12.6s
791: learn: 0.2638795 total: 43.7s remaining: 12.6s
792: learn: 0.2638349 total: 43.8s remaining: 12.5s
793: learn: 0.2637079 total: 43.8s remaining: 12.5s
794: learn: 0.2637035 total: 43.9s remaining: 12.4s
795: learn: 0.2635223 total: 43.9s remaining: 12.4s
796: learn: 0.2634472 total: 44s remaining: 12.3s
797: learn: 0.2633916 total: 44.1s remaining: 12.3s
798: learn: 0.2633173 total: 44.1s remaining: 12.2s
799: learn: 0.2631439 total: 44.2s remaining: 12.1s
800: learn: 0.2630792 total: 44.2s remaining: 12.1s
801: learn: 0.2630576 total: 44.3s remaining: 12s
802: learn: 0.2629694 total: 44.4s remaining: 12s
803: learn: 0.2629462 total: 44.4s remaining: 11.9s
804: learn: 0.2629451 total: 44.5s remaining: 11.9s
805: learn: 0.2629450 total: 44.5s remaining: 11.8s
806: learn: 0.2629361 total: 44.6s remaining: 11.8s
807: learn: 0.2627413 total: 44.6s remaining: 11.7s
808: learn: 0.2627109 total: 44.7s remaining: 11.7s
809: learn: 0.2626623 total: 44.8s remaining: 11.6s
810: learn: 0.2625636 total: 44.8s remaining: 11.6s
811: learn: 0.2625129 total: 44.9s remaining: 11.5s
812: learn: 0.2623651 total: 45s remaining: 11.5s
813: learn: 0.2623244 total: 45s remaining: 11.4s
814: learn: 0.2622047 total: 45.1s remaining: 11.3s
815: learn: 0.2621457 total: 45.2s remaining: 11.3s
816: learn: 0.2621068 total: 45.2s remaining: 11.2s
817: learn: 0.2620669 total: 45.3s remaining: 11.2s
818: learn: 0.2620068 total: 45.4s remaining: 11.1s
819: learn: 0.2619813 total: 45.4s remaining: 11.1s
820: learn: 0.2619807 total: 45.5s remaining: 11s
821: learn: 0.2618952 total: 45.5s remaining: 11s
822: learn: 0.2618084 total: 45.6s remaining: 10.9s
823: learn: 0.2617072 total: 45.7s remaining: 10.9s
824: learn: 0.2615802 total: 45.7s remaining: 10.8s
825: learn: 0.2615053 total: 45.8s remaining: 10.8s
826: learn: 0.2614003 total: 45.8s remaining: 10.7s
827: learn: 0.2613173 total: 45.9s remaining: 10.6s
828: learn: 0.2612676 total: 46s remaining: 10.6s
829: learn: 0.2612453 total: 46s remaining: 10.5s
830: learn: 0.2611857 total: 46.1s remaining: 10.5s
831: learn: 0.2611368 total: 46.2s remaining: 10.4s
832: learn: 0.2611055 total: 46.2s remaining: 10.4s
833: learn: 0.2610954 total: 46.3s remaining: 10.3s
834: learn: 0.2610544 total: 46.3s remaining: 10.3s
835: learn: 0.2610529 total: 46.4s remaining: 10.2s
836: learn: 0.2610528 total: 46.4s remaining: 10.2s
837: learn: 0.2609830 total: 46.5s remaining: 10.1s
838: learn: 0.2609829 total: 46.5s remaining: 10s
839: learn: 0.2609425 total: 46.6s remaining: 9.98s
840: learn: 0.2608555 total: 46.6s remaining: 9.93s
841: learn: 0.2608268 total: 46.7s remaining: 9.87s
842: learn: 0.2607636 total: 46.8s remaining: 9.82s
843: learn: 0.2607323 total: 46.8s remaining: 9.77s
844: learn: 0.2607075 total: 46.9s remaining: 9.71s
845: learn: 0.2606842 total: 47s remaining: 9.66s
846: learn: 0.2606413 total: 47s remaining: 9.6s
847: learn: 0.2606006 total: 47.1s remaining: 9.55s
848: learn: 0.2605175 total: 47.1s remaining: 9.49s
849: learn: 0.2603355 total: 47.2s remaining: 9.44s
850: learn: 0.2602892 total: 47.3s remaining: 9.39s
851: learn: 0.2602341 total: 47.3s remaining: 9.33s
852: learn: 0.2602301 total: 47.4s remaining: 9.28s
853: learn: 0.2602115 total: 47.4s remaining: 9.22s
854: learn: 0.2601493 total: 47.5s remaining: 9.16s
855: learn: 0.2600862 total: 47.5s remaining: 9.11s
856: learn: 0.2600850 total: 47.6s remaining: 9.05s
857: learn: 0.2600593 total: 47.6s remaining: 8.99s
858: learn: 0.2600290 total: 47.7s remaining: 8.94s
859: learn: 0.2600273 total: 47.8s remaining: 8.88s
860: learn: 0.2600255 total: 47.8s remaining: 8.83s
861: learn: 0.2599753 total: 47.9s remaining: 8.77s
862: learn: 0.2599632 total: 47.9s remaining: 8.72s
863: learn: 0.2598432 total: 48s remaining: 8.66s
864: learn: 0.2597892 total: 48s remaining: 8.6s
865: learn: 0.2596812 total: 48.1s remaining: 8.55s
866: learn: 0.2596085 total: 48.1s remaining: 8.49s
867: learn: 0.2595569 total: 48.2s remaining: 8.44s
868: learn: 0.2595552 total: 48.2s remaining: 8.38s
869: learn: 0.2595037 total: 48.3s remaining: 8.32s
870: learn: 0.2594964 total: 48.3s remaining: 8.27s
871: learn: 0.2594962 total: 48.4s remaining: 8.21s
872: learn: 0.2594686 total: 48.4s remaining: 8.15s
873: learn: 0.2593672 total: 48.5s remaining: 8.1s
874: learn: 0.2592654 total: 48.5s remaining: 8.04s
875: learn: 0.2592648 total: 48.6s remaining: 7.98s
876: learn: 0.2591809 total: 48.6s remaining: 7.93s
877: learn: 0.2590246 total: 48.7s remaining: 7.87s
878: learn: 0.2589172 total: 48.7s remaining: 7.82s
879: learn: 0.2588234 total: 48.8s remaining: 7.76s
880: learn: 0.2588118 total: 48.8s remaining: 7.71s
881: learn: 0.2587172 total: 48.9s remaining: 7.65s
882: learn: 0.2587110 total: 48.9s remaining: 7.59s
883: learn: 0.2585794 total: 49s remaining: 7.54s
884: learn: 0.2585783 total: 49s remaining: 7.48s
885: learn: 0.2585783 total: 49s remaining: 7.42s
886: learn: 0.2584873 total: 49.1s remaining: 7.36s
887: learn: 0.2584858 total: 49.2s remaining: 7.31s
888: learn: 0.2584600 total: 49.2s remaining: 7.25s
889: learn: 0.2584450 total: 49.3s remaining: 7.2s
890: learn: 0.2584025 total: 49.3s remaining: 7.14s
891: learn: 0.2583802 total: 49.4s remaining: 7.08s
892: learn: 0.2583073 total: 49.4s remaining: 7.03s
893: learn: 0.2581858 total: 49.5s remaining: 6.97s
894: learn: 0.2581744 total: 49.5s remaining: 6.92s
895: learn: 0.2581154 total: 49.6s remaining: 6.86s
896: learn: 0.2580997 total: 49.6s remaining: 6.8s
897: learn: 0.2580199 total: 49.7s remaining: 6.75s
898: learn: 0.2579236 total: 49.7s remaining: 6.7s
899: learn: 0.2579007 total: 49.8s remaining: 6.64s
900: learn: 0.2578571 total: 49.9s remaining: 6.58s
901: learn: 0.2577351 total: 49.9s remaining: 6.53s
902: learn: 0.2577324 total: 50s remaining: 6.47s
903: learn: 0.2576536 total: 50s remaining: 6.42s
904: learn: 0.2576507 total: 50.1s remaining: 6.36s
905: learn: 0.2576079 total: 50.1s remaining: 6.31s
906: learn: 0.2576078 total: 50.2s remaining: 6.25s
907: learn: 0.2574887 total: 50.2s remaining: 6.19s
908: learn: 0.2572139 total: 50.3s remaining: 6.14s
909: learn: 0.2572138 total: 50.3s remaining: 6.08s
910: learn: 0.2571909 total: 50.3s remaining: 6.02s
911: learn: 0.2571289 total: 50.4s remaining: 5.97s
912: learn: 0.2571289 total: 50.4s remaining: 5.91s
913: learn: 0.2569711 total: 50.5s remaining: 5.85s
914: learn: 0.2569166 total: 50.5s remaining: 5.8s
915: learn: 0.2569134 total: 50.6s remaining: 5.74s
916: learn: 0.2568376 total: 50.6s remaining: 5.68s
917: learn: 0.2567907 total: 50.7s remaining: 5.63s
918: learn: 0.2567445 total: 50.7s remaining: 5.57s
919: learn: 0.2567328 total: 50.8s remaining: 5.52s
920: learn: 0.2567229 total: 50.8s remaining: 5.46s
921: learn: 0.2567132 total: 50.9s remaining: 5.41s
922: learn: 0.2566725 total: 51s remaining: 5.36s
923: learn: 0.2566713 total: 51s remaining: 5.3s
924: learn: 0.2565546 total: 51.1s remaining: 5.25s
925: learn: 0.2565008 total: 51.1s remaining: 5.19s
926: learn: 0.2565007 total: 51.2s remaining: 5.13s
927: learn: 0.2564609 total: 51.3s remaining: 5.08s
928: learn: 0.2564361 total: 51.3s remaining: 5.03s
929: learn: 0.2563980 total: 51.4s remaining: 4.97s
930: learn: 0.2563707 total: 51.4s remaining: 4.92s
931: learn: 0.2562813 total: 51.5s remaining: 4.86s
932: learn: 0.2562209 total: 51.6s remaining: 4.81s
933: learn: 0.2561281 total: 51.6s remaining: 4.75s
934: learn: 0.2560471 total: 51.7s remaining: 4.7s
935: learn: 0.2560359 total: 51.8s remaining: 4.64s
936: learn: 0.2559492 total: 51.8s remaining: 4.59s
937: learn: 0.2559082 total: 51.9s remaining: 4.54s
938: learn: 0.2558745 total: 51.9s remaining: 4.48s
939: learn: 0.2557954 total: 52s remaining: 4.42s
940: learn: 0.2557950 total: 52s remaining: 4.37s
941: learn: 0.2556620 total: 52.1s remaining: 4.31s
942: learn: 0.2556487 total: 52.2s remaining: 4.26s
943: learn: 0.2556221 total: 52.2s remaining: 4.2s
944: learn: 0.2555649 total: 52.3s remaining: 4.15s
945: learn: 0.2554653 total: 52.3s remaining: 4.09s
946: learn: 0.2553960 total: 52.4s remaining: 4.04s
947: learn: 0.2553766 total: 52.5s remaining: 3.98s
948: learn: 0.2553761 total: 52.5s remaining: 3.93s
949: learn: 0.2553031 total: 52.6s remaining: 3.88s
950: learn: 0.2552980 total: 52.7s remaining: 3.82s
951: learn: 0.2552850 total: 52.7s remaining: 3.77s
952: learn: 0.2552179 total: 52.8s remaining: 3.71s
953: learn: 0.2552018 total: 52.8s remaining: 3.65s
954: learn: 0.2551817 total: 52.9s remaining: 3.6s
955: learn: 0.2551817 total: 52.9s remaining: 3.54s
956: learn: 0.2551698 total: 53s remaining: 3.49s
957: learn: 0.2550823 total: 53.1s remaining: 3.43s
958: learn: 0.2550270 total: 53.1s remaining: 3.38s
959: learn: 0.2549225 total: 53.2s remaining: 3.32s
960: learn: 0.2549211 total: 53.2s remaining: 3.27s
961: learn: 0.2549198 total: 53.3s remaining: 3.21s
962: learn: 0.2547374 total: 53.3s remaining: 3.16s
963: learn: 0.2547365 total: 53.4s remaining: 3.1s
964: learn: 0.2547354 total: 53.5s remaining: 3.05s
965: learn: 0.2546493 total: 53.5s remaining: 2.99s
966: learn: 0.2546075 total: 53.6s remaining: 2.94s
967: learn: 0.2545612 total: 53.7s remaining: 2.88s
968: learn: 0.2545573 total: 53.7s remaining: 2.83s
969: learn: 0.2545431 total: 53.8s remaining: 2.77s
970: learn: 0.2545301 total: 53.9s remaining: 2.72s
971: learn: 0.2544787 total: 53.9s remaining: 2.66s
972: learn: 0.2544449 total: 54s remaining: 2.61s
973: learn: 0.2543483 total: 54.1s remaining: 2.55s
974: learn: 0.2543264 total: 54.1s remaining: 2.5s
975: learn: 0.2543255 total: 54.2s remaining: 2.44s
976: learn: 0.2542299 total: 54.3s remaining: 2.39s
977: learn: 0.2541973 total: 54.3s remaining: 2.33s
978: learn: 0.2541662 total: 54.4s remaining: 2.28s
979: learn: 0.2540914 total: 54.4s remaining: 2.22s
980: learn: 0.2540168 total: 54.5s remaining: 2.17s
981: learn: 0.2539119 total: 54.5s remaining: 2.11s
982: learn: 0.2539119 total: 54.5s remaining: 2.05s
983: learn: 0.2539116 total: 54.6s remaining: 2s
984: learn: 0.2539109 total: 54.7s remaining: 1.94s
985: learn: 0.2539099 total: 54.7s remaining: 1.89s
986: learn: 0.2539095 total: 54.8s remaining: 1.83s
987: learn: 0.2539093 total: 54.8s remaining: 1.77s
988: learn: 0.2539088 total: 54.9s remaining: 1.72s
989: learn: 0.2538595 total: 54.9s remaining: 1.66s
990: learn: 0.2537864 total: 55s remaining: 1.61s
991: learn: 0.2537717 total: 55s remaining: 1.55s
992: learn: 0.2537427 total: 55.1s remaining: 1.5s
993: learn: 0.2537003 total: 55.1s remaining: 1.44s
994: learn: 0.2537000 total: 55.2s remaining: 1.39s
995: learn: 0.2536196 total: 55.2s remaining: 1.33s
996: learn: 0.2536185 total: 55.3s remaining: 1.27s
997: learn: 0.2535211 total: 55.3s remaining: 1.22s
998: learn: 0.2535024 total: 55.4s remaining: 1.16s
999: learn: 0.2534235 total: 55.4s remaining: 1.11s
1000: learn: 0.2533928 total: 55.5s remaining: 1.05s
1001: learn: 0.2533662 total: 55.5s remaining: 998ms
1002: learn: 0.2533649 total: 55.6s remaining: 942ms
1003: learn: 0.2533085 total: 55.6s remaining: 887ms
1004: learn: 0.2533077 total: 55.7s remaining: 831ms
1005: learn: 0.2533076 total: 55.7s remaining: 776ms
1006: learn: 0.2532919 total: 55.8s remaining: 720ms
1007: learn: 0.2531933 total: 55.9s remaining: 665ms
1008: learn: 0.2531634 total: 55.9s remaining: 609ms
1009: learn: 0.2531622 total: 56s remaining: 554ms
1010: learn: 0.2531612 total: 56s remaining: 499ms
1011: learn: 0.2530085 total: 56.1s remaining: 443ms
1012: learn: 0.2529704 total: 56.1s remaining: 388ms
1013: learn: 0.2529459 total: 56.2s remaining: 332ms
1014: learn: 0.2528365 total: 56.2s remaining: 277ms
1015: learn: 0.2527583 total: 56.3s remaining: 222ms
1016: learn: 0.2527004 total: 56.3s remaining: 166ms
1017: learn: 0.2525747 total: 56.4s remaining: 111ms
1018: learn: 0.2525743 total: 56.4s remaining: 55.4ms
1019: learn: 0.2525564 total: 56.5s remaining: 0us
Finished training fold 5 - running score 0.8629349419105695
Running fold 6, 15737 train samples, 2622 validation samples
0: learn: 0.6484067 total: 54.4ms remaining: 55.5s
1: learn: 0.6099849 total: 79.2ms remaining: 40.3s
2: learn: 0.5764671 total: 136ms remaining: 46.1s
3: learn: 0.5477826 total: 188ms remaining: 47.7s
4: learn: 0.5234277 total: 239ms remaining: 48.5s
5: learn: 0.5019269 total: 290ms remaining: 49s
6: learn: 0.4832412 total: 339ms remaining: 49.1s
7: learn: 0.4676360 total: 395ms remaining: 50s
8: learn: 0.4538647 total: 451ms remaining: 50.6s
9: learn: 0.4421292 total: 506ms remaining: 51.1s
10: learn: 0.4318671 total: 558ms remaining: 51.2s
11: learn: 0.4228869 total: 612ms remaining: 51.4s
12: learn: 0.4152563 total: 664ms remaining: 51.5s
13: learn: 0.4086682 total: 716ms remaining: 51.4s
14: learn: 0.4028530 total: 781ms remaining: 52.3s
15: learn: 0.3978663 total: 850ms remaining: 53.4s
16: learn: 0.3934172 total: 908ms remaining: 53.6s
17: learn: 0.3895942 total: 964ms remaining: 53.7s
18: learn: 0.3861957 total: 1.02s remaining: 54s
19: learn: 0.3832409 total: 1.08s remaining: 54s
20: learn: 0.3807430 total: 1.13s remaining: 53.8s
21: learn: 0.3784542 total: 1.18s remaining: 53.6s
22: learn: 0.3764819 total: 1.23s remaining: 53.5s
23: learn: 0.3749065 total: 1.28s remaining: 53.3s
24: learn: 0.3733562 total: 1.33s remaining: 53.1s
25: learn: 0.3721220 total: 1.36s remaining: 52.1s
26: learn: 0.3710159 total: 1.42s remaining: 52.3s
27: learn: 0.3698875 total: 1.48s remaining: 52.3s
28: learn: 0.3688478 total: 1.53s remaining: 52.3s
29: learn: 0.3679451 total: 1.58s remaining: 52.2s
30: learn: 0.3671187 total: 1.63s remaining: 52.1s
31: learn: 0.3665087 total: 1.68s remaining: 52s
32: learn: 0.3659997 total: 1.71s remaining: 51.1s
33: learn: 0.3653739 total: 1.77s remaining: 51.3s
34: learn: 0.3649088 total: 1.82s remaining: 51.2s
35: learn: 0.3643893 total: 1.87s remaining: 51.2s
36: learn: 0.3640722 total: 1.89s remaining: 50.3s
37: learn: 0.3636717 total: 1.95s remaining: 50.3s
38: learn: 0.3632354 total: 2s remaining: 50.2s
39: learn: 0.3628800 total: 2.04s remaining: 50.1s
40: learn: 0.3625930 total: 2.09s remaining: 50s
41: learn: 0.3623266 total: 2.14s remaining: 49.9s
42: learn: 0.3619864 total: 2.19s remaining: 49.8s
43: learn: 0.3617484 total: 2.24s remaining: 49.8s
44: learn: 0.3613916 total: 2.29s remaining: 49.7s
45: learn: 0.3610558 total: 2.34s remaining: 49.6s
46: learn: 0.3608768 total: 2.39s remaining: 49.6s
47: learn: 0.3606110 total: 2.44s remaining: 49.5s
48: learn: 0.3603499 total: 2.5s remaining: 49.5s
49: learn: 0.3601362 total: 2.55s remaining: 49.5s
50: learn: 0.3599847 total: 2.6s remaining: 49.4s
51: learn: 0.3598263 total: 2.65s remaining: 49.3s
52: learn: 0.3594335 total: 2.7s remaining: 49.3s
53: learn: 0.3592137 total: 2.75s remaining: 49.2s
54: learn: 0.3589969 total: 2.8s remaining: 49.2s
55: learn: 0.3587812 total: 2.85s remaining: 49.1s
56: learn: 0.3584725 total: 2.9s remaining: 49.1s
57: learn: 0.3582850 total: 2.93s remaining: 48.7s
58: learn: 0.3580825 total: 2.98s remaining: 48.6s
59: learn: 0.3578988 total: 3.04s remaining: 48.6s
60: learn: 0.3576048 total: 3.09s remaining: 48.5s
61: learn: 0.3574829 total: 3.14s remaining: 48.5s
62: learn: 0.3571598 total: 3.19s remaining: 48.5s
63: learn: 0.3569963 total: 3.24s remaining: 48.5s
64: learn: 0.3567864 total: 3.29s remaining: 48.4s
65: learn: 0.3564666 total: 3.35s remaining: 48.5s
66: learn: 0.3562480 total: 3.42s remaining: 48.6s
67: learn: 0.3559832 total: 3.48s remaining: 48.7s
68: learn: 0.3557181 total: 3.56s remaining: 49.1s
69: learn: 0.3556058 total: 3.63s remaining: 49.3s
70: learn: 0.3554055 total: 3.7s remaining: 49.4s
71: learn: 0.3551258 total: 3.76s remaining: 49.6s
72: learn: 0.3548395 total: 3.84s remaining: 49.8s
73: learn: 0.3545594 total: 3.91s remaining: 50s
74: learn: 0.3543816 total: 3.98s remaining: 50.2s
75: learn: 0.3541932 total: 4.05s remaining: 50.3s
76: learn: 0.3538652 total: 4.11s remaining: 50.3s
77: learn: 0.3537278 total: 4.17s remaining: 50.4s
78: learn: 0.3534631 total: 4.24s remaining: 50.5s
79: learn: 0.3532699 total: 4.3s remaining: 50.6s
80: learn: 0.3530560 total: 4.37s remaining: 50.7s
81: learn: 0.3527576 total: 4.44s remaining: 50.8s
82: learn: 0.3526016 total: 4.51s remaining: 50.9s
83: learn: 0.3523887 total: 4.58s remaining: 51.1s
84: learn: 0.3522113 total: 4.65s remaining: 51.1s
85: learn: 0.3520651 total: 4.71s remaining: 51.2s
86: learn: 0.3519327 total: 4.79s remaining: 51.3s
87: learn: 0.3518148 total: 4.86s remaining: 51.4s
88: learn: 0.3516816 total: 4.93s remaining: 51.6s
89: learn: 0.3514482 total: 5s remaining: 51.7s
90: learn: 0.3511707 total: 5.06s remaining: 51.7s
91: learn: 0.3508912 total: 5.13s remaining: 51.8s
92: learn: 0.3506149 total: 5.2s remaining: 51.8s
93: learn: 0.3504823 total: 5.26s remaining: 51.8s
94: learn: 0.3502713 total: 5.32s remaining: 51.8s
95: learn: 0.3500618 total: 5.38s remaining: 51.8s
96: learn: 0.3498216 total: 5.44s remaining: 51.8s
97: learn: 0.3495973 total: 5.51s remaining: 51.8s
98: learn: 0.3494131 total: 5.57s remaining: 51.8s
99: learn: 0.3491107 total: 5.63s remaining: 51.8s
100: learn: 0.3490873 total: 5.67s remaining: 51.6s
101: learn: 0.3488851 total: 5.73s remaining: 51.6s
102: learn: 0.3486473 total: 5.79s remaining: 51.5s
103: learn: 0.3485507 total: 5.85s remaining: 51.5s
104: learn: 0.3483965 total: 5.91s remaining: 51.5s
105: learn: 0.3482695 total: 5.97s remaining: 51.5s
106: learn: 0.3480506 total: 6.04s remaining: 51.5s
107: learn: 0.3477509 total: 6.1s remaining: 51.5s
108: learn: 0.3476088 total: 6.16s remaining: 51.5s
109: learn: 0.3473267 total: 6.22s remaining: 51.5s
110: learn: 0.3470858 total: 6.28s remaining: 51.5s
111: learn: 0.3468812 total: 6.34s remaining: 51.4s
112: learn: 0.3467424 total: 6.41s remaining: 51.4s
113: learn: 0.3464319 total: 6.46s remaining: 51.4s
114: learn: 0.3462382 total: 6.53s remaining: 51.4s
115: learn: 0.3459252 total: 6.59s remaining: 51.4s
116: learn: 0.3457059 total: 6.66s remaining: 51.4s
117: learn: 0.3456376 total: 6.72s remaining: 51.4s
118: learn: 0.3455179 total: 6.77s remaining: 51.3s
119: learn: 0.3452963 total: 6.82s remaining: 51.2s
120: learn: 0.3449945 total: 6.87s remaining: 51s
121: learn: 0.3447568 total: 6.92s remaining: 51s
122: learn: 0.3444046 total: 6.98s remaining: 50.9s
123: learn: 0.3442111 total: 7.03s remaining: 50.8s
124: learn: 0.3439833 total: 7.08s remaining: 50.7s
125: learn: 0.3437557 total: 7.13s remaining: 50.6s
126: learn: 0.3435923 total: 7.18s remaining: 50.5s
127: learn: 0.3433986 total: 7.23s remaining: 50.4s
128: learn: 0.3433055 total: 7.28s remaining: 50.3s
129: learn: 0.3431494 total: 7.33s remaining: 50.2s
130: learn: 0.3427734 total: 7.38s remaining: 50.1s
131: learn: 0.3426614 total: 7.43s remaining: 50s
132: learn: 0.3424758 total: 7.48s remaining: 49.9s
133: learn: 0.3422990 total: 7.63s remaining: 50.4s
134: learn: 0.3420791 total: 7.69s remaining: 50.4s
135: learn: 0.3418417 total: 7.75s remaining: 50.3s
136: learn: 0.3416229 total: 7.8s remaining: 50.3s
137: learn: 0.3413352 total: 7.85s remaining: 50.2s
138: learn: 0.3410292 total: 7.9s remaining: 50.1s
139: learn: 0.3409137 total: 7.95s remaining: 50s
140: learn: 0.3407752 total: 8s remaining: 49.9s
141: learn: 0.3405926 total: 8.05s remaining: 49.8s
142: learn: 0.3404342 total: 8.1s remaining: 49.7s
143: learn: 0.3401268 total: 8.15s remaining: 49.6s
144: learn: 0.3399864 total: 8.2s remaining: 49.5s
145: learn: 0.3398413 total: 8.26s remaining: 49.4s
146: learn: 0.3396524 total: 8.31s remaining: 49.3s
147: learn: 0.3394703 total: 8.35s remaining: 49.2s
148: learn: 0.3392545 total: 8.41s remaining: 49.1s
149: learn: 0.3390023 total: 8.46s remaining: 49s
150: learn: 0.3387685 total: 8.51s remaining: 49s
151: learn: 0.3385295 total: 8.56s remaining: 48.9s
152: learn: 0.3383383 total: 8.61s remaining: 48.8s
153: learn: 0.3382148 total: 8.66s remaining: 48.7s
154: learn: 0.3380865 total: 8.71s remaining: 48.6s
155: learn: 0.3378596 total: 8.76s remaining: 48.5s
156: learn: 0.3376287 total: 8.81s remaining: 48.4s
157: learn: 0.3375021 total: 8.87s remaining: 48.4s
158: learn: 0.3374029 total: 8.91s remaining: 48.3s
159: learn: 0.3371923 total: 8.96s remaining: 48.2s
160: learn: 0.3370462 total: 9.02s remaining: 48.1s
161: learn: 0.3368386 total: 9.06s remaining: 48s
162: learn: 0.3367335 total: 9.11s remaining: 47.9s
163: learn: 0.3365921 total: 9.16s remaining: 47.8s
164: learn: 0.3363340 total: 9.21s remaining: 47.8s
165: learn: 0.3360622 total: 9.27s remaining: 47.7s
166: learn: 0.3359097 total: 9.32s remaining: 47.6s
167: learn: 0.3358199 total: 9.37s remaining: 47.5s
168: learn: 0.3356408 total: 9.42s remaining: 47.5s
169: learn: 0.3354596 total: 9.48s remaining: 47.4s
170: learn: 0.3352786 total: 9.53s remaining: 47.3s
171: learn: 0.3350350 total: 9.58s remaining: 47.2s
172: learn: 0.3348262 total: 9.63s remaining: 47.1s
173: learn: 0.3346012 total: 9.68s remaining: 47.1s
174: learn: 0.3344194 total: 9.73s remaining: 47s
175: learn: 0.3342855 total: 9.78s remaining: 46.9s
176: learn: 0.3341697 total: 9.84s remaining: 46.8s
177: learn: 0.3339388 total: 9.89s remaining: 46.8s
178: learn: 0.3337572 total: 9.94s remaining: 46.7s
179: learn: 0.3336144 total: 9.99s remaining: 46.6s
180: learn: 0.3334634 total: 10s remaining: 46.6s
181: learn: 0.3332796 total: 10.1s remaining: 46.5s
182: learn: 0.3330143 total: 10.1s remaining: 46.4s
183: learn: 0.3327314 total: 10.2s remaining: 46.3s
184: learn: 0.3325747 total: 10.2s remaining: 46.2s
185: learn: 0.3323839 total: 10.3s remaining: 46.2s
186: learn: 0.3322064 total: 10.3s remaining: 46.1s
187: learn: 0.3320684 total: 10.4s remaining: 46s
188: learn: 0.3317541 total: 10.4s remaining: 45.9s
189: learn: 0.3316814 total: 10.5s remaining: 45.9s
190: learn: 0.3316180 total: 10.5s remaining: 45.8s
191: learn: 0.3314286 total: 10.6s remaining: 45.7s
192: learn: 0.3312757 total: 10.6s remaining: 45.6s
193: learn: 0.3311229 total: 10.7s remaining: 45.5s
194: learn: 0.3309607 total: 10.7s remaining: 45.5s
195: learn: 0.3308040 total: 10.8s remaining: 45.4s
196: learn: 0.3304521 total: 10.8s remaining: 45.3s
197: learn: 0.3302357 total: 10.9s remaining: 45.2s
198: learn: 0.3299666 total: 10.9s remaining: 45.2s
199: learn: 0.3298025 total: 11s remaining: 45.1s
200: learn: 0.3295639 total: 11.1s remaining: 45s
201: learn: 0.3293192 total: 11.1s remaining: 45s
202: learn: 0.3291228 total: 11.2s remaining: 44.9s
203: learn: 0.3288501 total: 11.2s remaining: 44.9s
204: learn: 0.3286995 total: 11.3s remaining: 44.9s
205: learn: 0.3283299 total: 11.4s remaining: 44.9s
206: learn: 0.3281826 total: 11.4s remaining: 44.8s
207: learn: 0.3280259 total: 11.5s remaining: 44.8s
208: learn: 0.3279160 total: 11.5s remaining: 44.8s
209: learn: 0.3276787 total: 11.6s remaining: 44.8s
210: learn: 0.3275322 total: 11.7s remaining: 44.7s
211: learn: 0.3274149 total: 11.7s remaining: 44.7s
212: learn: 0.3271432 total: 11.8s remaining: 44.7s
213: learn: 0.3270099 total: 11.9s remaining: 44.6s
214: learn: 0.3268478 total: 11.9s remaining: 44.6s
215: learn: 0.3266781 total: 12s remaining: 44.6s
216: learn: 0.3263968 total: 12s remaining: 44.6s
217: learn: 0.3262058 total: 12.1s remaining: 44.6s
218: learn: 0.3260033 total: 12.2s remaining: 44.5s
219: learn: 0.3258700 total: 12.2s remaining: 44.5s
220: learn: 0.3257109 total: 12.3s remaining: 44.5s
221: learn: 0.3254575 total: 12.4s remaining: 44.4s
222: learn: 0.3251469 total: 12.4s remaining: 44.4s
223: learn: 0.3249970 total: 12.5s remaining: 44.4s
224: learn: 0.3247955 total: 12.5s remaining: 44.3s
225: learn: 0.3247194 total: 12.6s remaining: 44.3s
226: learn: 0.3246104 total: 12.7s remaining: 44.3s
227: learn: 0.3244645 total: 12.7s remaining: 44.2s
228: learn: 0.3243191 total: 12.8s remaining: 44.2s
229: learn: 0.3241488 total: 12.9s remaining: 44.2s
230: learn: 0.3240277 total: 12.9s remaining: 44.1s
231: learn: 0.3238149 total: 13s remaining: 44.1s
232: learn: 0.3236874 total: 13.1s remaining: 44.1s
233: learn: 0.3234387 total: 13.1s remaining: 44.1s
234: learn: 0.3232963 total: 13.2s remaining: 44.1s
235: learn: 0.3229468 total: 13.3s remaining: 44s
236: learn: 0.3225792 total: 13.3s remaining: 44s
237: learn: 0.3224473 total: 13.4s remaining: 43.9s
238: learn: 0.3221504 total: 13.4s remaining: 43.9s
239: learn: 0.3219699 total: 13.5s remaining: 43.9s
240: learn: 0.3218506 total: 13.6s remaining: 43.8s
241: learn: 0.3216938 total: 13.6s remaining: 43.8s
242: learn: 0.3213202 total: 13.7s remaining: 43.7s
243: learn: 0.3211284 total: 13.7s remaining: 43.7s
244: learn: 0.3209729 total: 13.8s remaining: 43.7s
245: learn: 0.3208830 total: 13.9s remaining: 43.6s
246: learn: 0.3207881 total: 13.9s remaining: 43.6s
247: learn: 0.3204611 total: 14s remaining: 43.5s
248: learn: 0.3202664 total: 14s remaining: 43.5s
249: learn: 0.3201836 total: 14.1s remaining: 43.4s
250: learn: 0.3199512 total: 14.2s remaining: 43.4s
251: learn: 0.3198612 total: 14.2s remaining: 43.4s
252: learn: 0.3195557 total: 14.3s remaining: 43.3s
253: learn: 0.3194271 total: 14.3s remaining: 43.3s
254: learn: 0.3192654 total: 14.4s remaining: 43.2s
255: learn: 0.3189767 total: 14.5s remaining: 43.2s
256: learn: 0.3188137 total: 14.5s remaining: 43.2s
257: learn: 0.3186678 total: 14.6s remaining: 43.1s
258: learn: 0.3185043 total: 14.7s remaining: 43.1s
259: learn: 0.3182487 total: 14.7s remaining: 43s
260: learn: 0.3180058 total: 14.8s remaining: 42.9s
261: learn: 0.3177335 total: 14.8s remaining: 42.8s
262: learn: 0.3176431 total: 14.9s remaining: 42.8s
263: learn: 0.3172929 total: 14.9s remaining: 42.7s
264: learn: 0.3170527 total: 15s remaining: 42.6s
265: learn: 0.3169142 total: 15s remaining: 42.6s
266: learn: 0.3167836 total: 15.1s remaining: 42.5s
267: learn: 0.3166549 total: 15.1s remaining: 42.4s
268: learn: 0.3164917 total: 15.2s remaining: 42.4s
269: learn: 0.3164241 total: 15.2s remaining: 42.3s
270: learn: 0.3162384 total: 15.3s remaining: 42.2s
271: learn: 0.3161662 total: 15.3s remaining: 42.1s
272: learn: 0.3159916 total: 15.4s remaining: 42.1s
273: learn: 0.3158181 total: 15.4s remaining: 42s
274: learn: 0.3155591 total: 15.5s remaining: 41.9s
275: learn: 0.3153218 total: 15.5s remaining: 41.8s
276: learn: 0.3150984 total: 15.6s remaining: 41.8s
277: learn: 0.3148794 total: 15.6s remaining: 41.7s
278: learn: 0.3147016 total: 15.7s remaining: 41.6s
279: learn: 0.3145690 total: 15.7s remaining: 41.6s
280: learn: 0.3144342 total: 15.8s remaining: 41.5s
281: learn: 0.3143370 total: 15.8s remaining: 41.4s
282: learn: 0.3141581 total: 15.9s remaining: 41.3s
283: learn: 0.3139823 total: 15.9s remaining: 41.3s
284: learn: 0.3137900 total: 16s remaining: 41.2s
285: learn: 0.3135854 total: 16s remaining: 41.1s
286: learn: 0.3134108 total: 16.1s remaining: 41s
287: learn: 0.3132643 total: 16.1s remaining: 41s
288: learn: 0.3131054 total: 16.2s remaining: 40.9s
289: learn: 0.3128992 total: 16.2s remaining: 40.8s
290: learn: 0.3126363 total: 16.3s remaining: 40.8s
291: learn: 0.3124930 total: 16.3s remaining: 40.7s
292: learn: 0.3123488 total: 16.4s remaining: 40.6s
293: learn: 0.3121571 total: 16.4s remaining: 40.6s
294: learn: 0.3120962 total: 16.5s remaining: 40.5s
295: learn: 0.3119957 total: 16.5s remaining: 40.4s
296: learn: 0.3118555 total: 16.6s remaining: 40.4s
297: learn: 0.3116615 total: 16.6s remaining: 40.3s
298: learn: 0.3114572 total: 16.7s remaining: 40.2s
299: learn: 0.3112649 total: 16.7s remaining: 40.2s
300: learn: 0.3110530 total: 16.8s remaining: 40.1s
301: learn: 0.3108559 total: 16.8s remaining: 40.1s
302: learn: 0.3107289 total: 16.9s remaining: 40s
303: learn: 0.3106699 total: 17s remaining: 39.9s
304: learn: 0.3106001 total: 17s remaining: 39.9s
305: learn: 0.3104909 total: 17.1s remaining: 39.8s
306: learn: 0.3103358 total: 17.1s remaining: 39.7s
307: learn: 0.3101038 total: 17.2s remaining: 39.7s
308: learn: 0.3099424 total: 17.2s remaining: 39.6s
309: learn: 0.3098065 total: 17.3s remaining: 39.6s
310: learn: 0.3096787 total: 17.3s remaining: 39.5s
311: learn: 0.3095377 total: 17.4s remaining: 39.5s
312: learn: 0.3093862 total: 17.5s remaining: 39.4s
313: learn: 0.3092729 total: 17.5s remaining: 39.4s
314: learn: 0.3091494 total: 17.6s remaining: 39.3s
315: learn: 0.3088997 total: 17.6s remaining: 39.2s
316: learn: 0.3086539 total: 17.7s remaining: 39.2s
317: learn: 0.3083503 total: 17.7s remaining: 39.1s
318: learn: 0.3081900 total: 17.8s remaining: 39s
319: learn: 0.3076411 total: 17.8s remaining: 39s
320: learn: 0.3075250 total: 17.9s remaining: 38.9s
321: learn: 0.3073175 total: 17.9s remaining: 38.8s
322: learn: 0.3071190 total: 18s remaining: 38.8s
323: learn: 0.3069663 total: 18s remaining: 38.7s
324: learn: 0.3067076 total: 18.1s remaining: 38.6s
325: learn: 0.3065436 total: 18.1s remaining: 38.6s
326: learn: 0.3063747 total: 18.2s remaining: 38.5s
327: learn: 0.3063273 total: 18.2s remaining: 38.5s
328: learn: 0.3062201 total: 18.3s remaining: 38.5s
329: learn: 0.3060371 total: 18.4s remaining: 38.4s
330: learn: 0.3057370 total: 18.4s remaining: 38.4s
331: learn: 0.3054997 total: 18.5s remaining: 38.3s
332: learn: 0.3051198 total: 18.6s remaining: 38.3s
333: learn: 0.3048272 total: 18.6s remaining: 38.3s
334: learn: 0.3046160 total: 18.7s remaining: 38.3s
335: learn: 0.3043898 total: 18.8s remaining: 38.2s
336: learn: 0.3040991 total: 18.8s remaining: 38.2s
337: learn: 0.3039661 total: 18.9s remaining: 38.1s
338: learn: 0.3037905 total: 19s remaining: 38.1s
339: learn: 0.3036621 total: 19s remaining: 38.1s
340: learn: 0.3034677 total: 19.1s remaining: 38s
341: learn: 0.3033659 total: 19.1s remaining: 38s
342: learn: 0.3032771 total: 19.2s remaining: 37.9s
343: learn: 0.3032097 total: 19.3s remaining: 37.9s
344: learn: 0.3030853 total: 19.3s remaining: 37.8s
345: learn: 0.3029333 total: 19.4s remaining: 37.8s
346: learn: 0.3027627 total: 19.5s remaining: 37.8s
347: learn: 0.3025957 total: 19.5s remaining: 37.7s
348: learn: 0.3022778 total: 19.6s remaining: 37.7s
349: learn: 0.3021422 total: 19.7s remaining: 37.6s
350: learn: 0.3020085 total: 19.7s remaining: 37.6s
351: learn: 0.3019118 total: 19.8s remaining: 37.5s
352: learn: 0.3017825 total: 19.8s remaining: 37.5s
353: learn: 0.3016370 total: 19.9s remaining: 37.5s
354: learn: 0.3014874 total: 20s remaining: 37.4s
355: learn: 0.3011817 total: 20s remaining: 37.4s
356: learn: 0.3011003 total: 20.1s remaining: 37.3s
357: learn: 0.3010407 total: 20.2s remaining: 37.3s
358: learn: 0.3008642 total: 20.2s remaining: 37.2s
359: learn: 0.3005201 total: 20.3s remaining: 37.2s
360: learn: 0.3004182 total: 20.4s remaining: 37.2s
361: learn: 0.3001868 total: 20.5s remaining: 37.3s
362: learn: 0.3001336 total: 20.6s remaining: 37.2s
363: learn: 0.2999694 total: 20.6s remaining: 37.2s
364: learn: 0.2999025 total: 20.7s remaining: 37.1s
365: learn: 0.2995766 total: 20.7s remaining: 37.1s
366: learn: 0.2995098 total: 20.8s remaining: 37s
367: learn: 0.2994764 total: 20.9s remaining: 37s
368: learn: 0.2993565 total: 20.9s remaining: 36.9s
369: learn: 0.2992203 total: 21s remaining: 36.9s
370: learn: 0.2989567 total: 21s remaining: 36.8s
371: learn: 0.2988761 total: 21.1s remaining: 36.7s
372: learn: 0.2987162 total: 21.2s remaining: 36.7s
373: learn: 0.2984408 total: 21.2s remaining: 36.6s
374: learn: 0.2982670 total: 21.3s remaining: 36.6s
375: learn: 0.2981508 total: 21.3s remaining: 36.6s
376: learn: 0.2980591 total: 21.4s remaining: 36.5s
377: learn: 0.2979950 total: 21.5s remaining: 36.5s
378: learn: 0.2978149 total: 21.5s remaining: 36.4s
379: learn: 0.2976985 total: 21.6s remaining: 36.4s
380: learn: 0.2975823 total: 21.7s remaining: 36.4s
381: learn: 0.2974985 total: 21.8s remaining: 36.3s
382: learn: 0.2972986 total: 21.8s remaining: 36.3s
383: learn: 0.2971109 total: 21.9s remaining: 36.2s
384: learn: 0.2970056 total: 21.9s remaining: 36.2s
385: learn: 0.2969836 total: 22s remaining: 36.1s
386: learn: 0.2969241 total: 22.1s remaining: 36.1s
387: learn: 0.2968653 total: 22.2s remaining: 36.1s
388: learn: 0.2967875 total: 22.2s remaining: 36s
389: learn: 0.2965767 total: 22.3s remaining: 36s
390: learn: 0.2964730 total: 22.4s remaining: 36s
391: learn: 0.2963783 total: 22.4s remaining: 35.9s
392: learn: 0.2962722 total: 22.5s remaining: 35.9s
393: learn: 0.2960786 total: 22.6s remaining: 35.9s
394: learn: 0.2959836 total: 22.7s remaining: 35.8s
395: learn: 0.2959269 total: 22.7s remaining: 35.8s
396: learn: 0.2954627 total: 22.8s remaining: 35.7s
397: learn: 0.2953106 total: 22.8s remaining: 35.7s
398: learn: 0.2951070 total: 22.9s remaining: 35.6s
399: learn: 0.2950378 total: 22.9s remaining: 35.5s
400: learn: 0.2948748 total: 23s remaining: 35.5s
401: learn: 0.2948385 total: 23s remaining: 35.4s
402: learn: 0.2947233 total: 23.1s remaining: 35.4s
403: learn: 0.2945622 total: 23.1s remaining: 35.3s
404: learn: 0.2944582 total: 23.2s remaining: 35.2s
405: learn: 0.2942913 total: 23.3s remaining: 35.2s
406: learn: 0.2941812 total: 23.3s remaining: 35.1s
407: learn: 0.2941323 total: 23.4s remaining: 35s
408: learn: 0.2940495 total: 23.4s remaining: 35s
409: learn: 0.2940122 total: 23.5s remaining: 34.9s
410: learn: 0.2937426 total: 23.5s remaining: 34.8s
411: learn: 0.2936203 total: 23.6s remaining: 34.8s
412: learn: 0.2935031 total: 23.6s remaining: 34.7s
413: learn: 0.2934082 total: 23.7s remaining: 34.7s
414: learn: 0.2933168 total: 23.7s remaining: 34.6s
415: learn: 0.2932236 total: 23.8s remaining: 34.6s
416: learn: 0.2930703 total: 23.9s remaining: 34.5s
417: learn: 0.2929695 total: 23.9s remaining: 34.4s
418: learn: 0.2928851 total: 24s remaining: 34.4s
419: learn: 0.2928142 total: 24s remaining: 34.3s
420: learn: 0.2927174 total: 24.1s remaining: 34.3s
421: learn: 0.2925334 total: 24.1s remaining: 34.2s
422: learn: 0.2924563 total: 24.2s remaining: 34.1s
423: learn: 0.2923709 total: 24.2s remaining: 34.1s
424: learn: 0.2922855 total: 24.3s remaining: 34s
425: learn: 0.2920793 total: 24.3s remaining: 33.9s
426: learn: 0.2920053 total: 24.4s remaining: 33.8s
427: learn: 0.2918646 total: 24.4s remaining: 33.8s
428: learn: 0.2918440 total: 24.5s remaining: 33.7s
429: learn: 0.2917244 total: 24.5s remaining: 33.6s
430: learn: 0.2915272 total: 24.6s remaining: 33.6s
431: learn: 0.2913310 total: 24.6s remaining: 33.5s
432: learn: 0.2912596 total: 24.7s remaining: 33.5s
433: learn: 0.2910783 total: 24.8s remaining: 33.4s
434: learn: 0.2908012 total: 24.8s remaining: 33.4s
435: learn: 0.2906221 total: 24.9s remaining: 33.3s
436: learn: 0.2903980 total: 24.9s remaining: 33.3s
437: learn: 0.2901927 total: 25s remaining: 33.2s
438: learn: 0.2900557 total: 25s remaining: 33.1s
439: learn: 0.2899294 total: 25.1s remaining: 33.1s
440: learn: 0.2896309 total: 25.2s remaining: 33s
441: learn: 0.2895244 total: 25.2s remaining: 33s
442: learn: 0.2894287 total: 25.3s remaining: 32.9s
443: learn: 0.2892342 total: 25.3s remaining: 32.8s
444: learn: 0.2891083 total: 25.4s remaining: 32.8s
445: learn: 0.2887273 total: 25.4s remaining: 32.7s
446: learn: 0.2885759 total: 25.5s remaining: 32.7s
447: learn: 0.2884492 total: 25.5s remaining: 32.6s
448: learn: 0.2883085 total: 25.6s remaining: 32.5s
449: learn: 0.2881787 total: 25.6s remaining: 32.5s
450: learn: 0.2881416 total: 25.7s remaining: 32.4s
451: learn: 0.2879607 total: 25.7s remaining: 32.4s
452: learn: 0.2878984 total: 25.8s remaining: 32.3s
453: learn: 0.2878075 total: 25.9s remaining: 32.2s
454: learn: 0.2876309 total: 25.9s remaining: 32.2s
455: learn: 0.2874897 total: 26s remaining: 32.1s
456: learn: 0.2873863 total: 26s remaining: 32s
457: learn: 0.2873344 total: 26.1s remaining: 32s
458: learn: 0.2872124 total: 26.1s remaining: 31.9s
459: learn: 0.2871288 total: 26.2s remaining: 31.9s
460: learn: 0.2869354 total: 26.3s remaining: 31.9s
461: learn: 0.2868793 total: 26.3s remaining: 31.8s
462: learn: 0.2867656 total: 26.4s remaining: 31.8s
463: learn: 0.2866223 total: 26.5s remaining: 31.7s
464: learn: 0.2865625 total: 26.5s remaining: 31.7s
465: learn: 0.2865119 total: 26.6s remaining: 31.6s
466: learn: 0.2864269 total: 26.7s remaining: 31.6s
467: learn: 0.2863730 total: 26.7s remaining: 31.5s
468: learn: 0.2862830 total: 26.8s remaining: 31.5s
469: learn: 0.2861712 total: 26.9s remaining: 31.4s
470: learn: 0.2860690 total: 27s remaining: 31.4s
471: learn: 0.2859093 total: 27s remaining: 31.4s
472: learn: 0.2858148 total: 27.1s remaining: 31.3s
473: learn: 0.2856811 total: 27.2s remaining: 31.3s
474: learn: 0.2855639 total: 27.2s remaining: 31.2s
475: learn: 0.2854376 total: 27.3s remaining: 31.2s
476: learn: 0.2854078 total: 27.4s remaining: 31.1s
477: learn: 0.2853128 total: 27.4s remaining: 31.1s
478: learn: 0.2852580 total: 27.5s remaining: 31.1s
479: learn: 0.2851244 total: 27.6s remaining: 31s
480: learn: 0.2850316 total: 27.6s remaining: 31s
481: learn: 0.2849592 total: 27.7s remaining: 30.9s
482: learn: 0.2847254 total: 27.8s remaining: 30.9s
483: learn: 0.2846285 total: 27.8s remaining: 30.8s
484: learn: 0.2845053 total: 27.9s remaining: 30.8s
485: learn: 0.2843596 total: 28s remaining: 30.7s
486: learn: 0.2842493 total: 28s remaining: 30.7s
487: learn: 0.2840487 total: 28.1s remaining: 30.6s
488: learn: 0.2839458 total: 28.2s remaining: 30.6s
489: learn: 0.2838621 total: 28.3s remaining: 30.6s
490: learn: 0.2837097 total: 28.3s remaining: 30.5s
491: learn: 0.2834028 total: 28.4s remaining: 30.5s
492: learn: 0.2832631 total: 28.5s remaining: 30.4s
493: learn: 0.2831855 total: 28.5s remaining: 30.4s
494: learn: 0.2829651 total: 28.6s remaining: 30.3s
495: learn: 0.2829181 total: 28.6s remaining: 30.3s
496: learn: 0.2827617 total: 28.7s remaining: 30.2s
497: learn: 0.2826120 total: 28.8s remaining: 30.2s
498: learn: 0.2825738 total: 28.8s remaining: 30.1s
499: learn: 0.2824638 total: 28.9s remaining: 30.1s
500: learn: 0.2823143 total: 29s remaining: 30s
501: learn: 0.2822106 total: 29s remaining: 29.9s
502: learn: 0.2819518 total: 29.1s remaining: 29.9s
503: learn: 0.2816307 total: 29.2s remaining: 29.8s
504: learn: 0.2815014 total: 29.2s remaining: 29.8s
505: learn: 0.2813931 total: 29.3s remaining: 29.7s
506: learn: 0.2813110 total: 29.4s remaining: 29.7s
507: learn: 0.2812706 total: 29.4s remaining: 29.6s
508: learn: 0.2812386 total: 29.5s remaining: 29.6s
509: learn: 0.2810756 total: 29.5s remaining: 29.5s
510: learn: 0.2810323 total: 29.6s remaining: 29.5s
511: learn: 0.2809717 total: 29.7s remaining: 29.4s
512: learn: 0.2808486 total: 29.7s remaining: 29.4s
513: learn: 0.2808045 total: 29.8s remaining: 29.3s
514: learn: 0.2807037 total: 29.8s remaining: 29.2s
515: learn: 0.2806242 total: 29.9s remaining: 29.2s
516: learn: 0.2804636 total: 29.9s remaining: 29.1s
517: learn: 0.2804558 total: 30s remaining: 29.1s
518: learn: 0.2804064 total: 30s remaining: 29s
519: learn: 0.2802032 total: 30.1s remaining: 28.9s
520: learn: 0.2800370 total: 30.1s remaining: 28.9s
521: learn: 0.2799695 total: 30.2s remaining: 28.8s
522: learn: 0.2799242 total: 30.3s remaining: 28.7s
523: learn: 0.2798220 total: 30.3s remaining: 28.7s
524: learn: 0.2796543 total: 30.4s remaining: 28.6s
525: learn: 0.2795650 total: 30.4s remaining: 28.6s
526: learn: 0.2795031 total: 30.5s remaining: 28.5s
527: learn: 0.2794111 total: 30.5s remaining: 28.4s
528: learn: 0.2793488 total: 30.6s remaining: 28.4s
529: learn: 0.2793200 total: 30.7s remaining: 28.3s
530: learn: 0.2792200 total: 30.7s remaining: 28.3s
531: learn: 0.2792195 total: 30.7s remaining: 28.2s
532: learn: 0.2790982 total: 30.8s remaining: 28.1s
533: learn: 0.2789161 total: 30.9s remaining: 28.1s
534: learn: 0.2787500 total: 30.9s remaining: 28s
535: learn: 0.2786291 total: 31s remaining: 28s
536: learn: 0.2785742 total: 31s remaining: 27.9s
537: learn: 0.2783381 total: 31.1s remaining: 27.8s
538: learn: 0.2781743 total: 31.1s remaining: 27.8s
539: learn: 0.2779796 total: 31.2s remaining: 27.7s
540: learn: 0.2779290 total: 31.2s remaining: 27.6s
541: learn: 0.2778490 total: 31.3s remaining: 27.6s
542: learn: 0.2777883 total: 31.3s remaining: 27.5s
543: learn: 0.2776733 total: 31.4s remaining: 27.5s
544: learn: 0.2775483 total: 31.4s remaining: 27.4s
545: learn: 0.2774914 total: 31.5s remaining: 27.3s
546: learn: 0.2773686 total: 31.5s remaining: 27.3s
547: learn: 0.2772247 total: 31.6s remaining: 27.2s
548: learn: 0.2771637 total: 31.6s remaining: 27.1s
549: learn: 0.2770311 total: 31.7s remaining: 27.1s
550: learn: 0.2769928 total: 31.7s remaining: 27s
551: learn: 0.2769026 total: 31.8s remaining: 26.9s
552: learn: 0.2768045 total: 31.8s remaining: 26.9s
553: learn: 0.2767009 total: 31.9s remaining: 26.8s
554: learn: 0.2766080 total: 31.9s remaining: 26.8s
555: learn: 0.2763747 total: 32s remaining: 26.7s
556: learn: 0.2763140 total: 32.1s remaining: 26.6s
557: learn: 0.2761266 total: 32.1s remaining: 26.6s
558: learn: 0.2760207 total: 32.2s remaining: 26.5s
559: learn: 0.2759108 total: 32.2s remaining: 26.5s
560: learn: 0.2757483 total: 32.3s remaining: 26.4s
561: learn: 0.2755013 total: 32.3s remaining: 26.4s
562: learn: 0.2754266 total: 32.4s remaining: 26.3s
563: learn: 0.2753152 total: 32.4s remaining: 26.2s
564: learn: 0.2752298 total: 32.5s remaining: 26.2s
565: learn: 0.2751638 total: 32.5s remaining: 26.1s
566: learn: 0.2750934 total: 32.6s remaining: 26s
567: learn: 0.2749728 total: 32.6s remaining: 26s
568: learn: 0.2748016 total: 32.7s remaining: 25.9s
569: learn: 0.2746830 total: 32.7s remaining: 25.8s
570: learn: 0.2746530 total: 32.8s remaining: 25.8s
571: learn: 0.2745214 total: 32.8s remaining: 25.7s
572: learn: 0.2743629 total: 32.9s remaining: 25.7s
573: learn: 0.2742584 total: 33s remaining: 25.7s
574: learn: 0.2741978 total: 33.1s remaining: 25.6s
575: learn: 0.2741178 total: 33.1s remaining: 25.6s
576: learn: 0.2740408 total: 33.2s remaining: 25.5s
577: learn: 0.2738496 total: 33.3s remaining: 25.4s
578: learn: 0.2737311 total: 33.3s remaining: 25.4s
579: learn: 0.2736977 total: 33.4s remaining: 25.3s
580: learn: 0.2735250 total: 33.5s remaining: 25.3s
581: learn: 0.2734604 total: 33.5s remaining: 25.2s
582: learn: 0.2733889 total: 33.6s remaining: 25.2s
583: learn: 0.2733397 total: 33.6s remaining: 25.1s
584: learn: 0.2731807 total: 33.7s remaining: 25.1s
585: learn: 0.2731573 total: 33.8s remaining: 25s
586: learn: 0.2730351 total: 33.8s remaining: 24.9s
587: learn: 0.2729334 total: 33.9s remaining: 24.9s
588: learn: 0.2728202 total: 33.9s remaining: 24.8s
589: learn: 0.2726832 total: 34s remaining: 24.8s
590: learn: 0.2726337 total: 34.1s remaining: 24.7s
591: learn: 0.2725606 total: 34.1s remaining: 24.7s
592: learn: 0.2724571 total: 34.2s remaining: 24.6s
593: learn: 0.2721476 total: 34.3s remaining: 24.6s
594: learn: 0.2718916 total: 34.3s remaining: 24.5s
595: learn: 0.2718157 total: 34.4s remaining: 24.5s
596: learn: 0.2717091 total: 34.4s remaining: 24.4s
597: learn: 0.2715807 total: 34.5s remaining: 24.3s
598: learn: 0.2715170 total: 34.6s remaining: 24.3s
599: learn: 0.2714735 total: 34.6s remaining: 24.2s
600: learn: 0.2713927 total: 34.7s remaining: 24.2s
601: learn: 0.2713745 total: 34.7s remaining: 24.1s
602: learn: 0.2712886 total: 34.8s remaining: 24.1s
603: learn: 0.2710336 total: 34.9s remaining: 24s
604: learn: 0.2709686 total: 34.9s remaining: 24s
605: learn: 0.2708837 total: 35s remaining: 23.9s
606: learn: 0.2707679 total: 35.1s remaining: 23.8s
607: learn: 0.2706805 total: 35.1s remaining: 23.8s
608: learn: 0.2705461 total: 35.2s remaining: 23.7s
609: learn: 0.2704545 total: 35.2s remaining: 23.7s
610: learn: 0.2704163 total: 35.3s remaining: 23.6s
611: learn: 0.2703259 total: 35.4s remaining: 23.6s
612: learn: 0.2701396 total: 35.4s remaining: 23.5s
613: learn: 0.2700703 total: 35.5s remaining: 23.5s
614: learn: 0.2700193 total: 35.6s remaining: 23.4s
615: learn: 0.2699419 total: 35.6s remaining: 23.4s
616: learn: 0.2698921 total: 35.7s remaining: 23.3s
617: learn: 0.2698120 total: 35.7s remaining: 23.2s
618: learn: 0.2697485 total: 35.8s remaining: 23.2s
619: learn: 0.2696673 total: 35.9s remaining: 23.1s
620: learn: 0.2695567 total: 35.9s remaining: 23.1s
621: learn: 0.2695204 total: 36s remaining: 23s
622: learn: 0.2693681 total: 36s remaining: 23s
623: learn: 0.2693055 total: 36.1s remaining: 22.9s
624: learn: 0.2692254 total: 36.2s remaining: 22.9s
625: learn: 0.2690834 total: 36.2s remaining: 22.8s
626: learn: 0.2690520 total: 36.3s remaining: 22.7s
627: learn: 0.2690284 total: 36.4s remaining: 22.7s
628: learn: 0.2689165 total: 36.4s remaining: 22.6s
629: learn: 0.2688633 total: 36.5s remaining: 22.6s
630: learn: 0.2687727 total: 36.5s remaining: 22.5s
631: learn: 0.2687110 total: 36.6s remaining: 22.4s
632: learn: 0.2686932 total: 36.6s remaining: 22.4s
633: learn: 0.2685948 total: 36.7s remaining: 22.3s
634: learn: 0.2685302 total: 36.7s remaining: 22.3s
635: learn: 0.2684023 total: 36.8s remaining: 22.2s
636: learn: 0.2682696 total: 36.8s remaining: 22.1s
637: learn: 0.2681796 total: 36.9s remaining: 22.1s
638: learn: 0.2680119 total: 36.9s remaining: 22s
639: learn: 0.2678233 total: 37s remaining: 21.9s
640: learn: 0.2678108 total: 37s remaining: 21.9s
641: learn: 0.2677126 total: 37.1s remaining: 21.8s
642: learn: 0.2676132 total: 37.1s remaining: 21.8s
643: learn: 0.2675230 total: 37.2s remaining: 21.7s
644: learn: 0.2674796 total: 37.2s remaining: 21.6s
645: learn: 0.2671670 total: 37.3s remaining: 21.6s
646: learn: 0.2670779 total: 37.3s remaining: 21.5s
647: learn: 0.2669427 total: 37.4s remaining: 21.5s
648: learn: 0.2668992 total: 37.4s remaining: 21.4s
649: learn: 0.2668097 total: 37.5s remaining: 21.3s
650: learn: 0.2667060 total: 37.5s remaining: 21.3s
651: learn: 0.2666302 total: 37.6s remaining: 21.2s
652: learn: 0.2664539 total: 37.6s remaining: 21.1s
653: learn: 0.2663946 total: 37.7s remaining: 21.1s
654: learn: 0.2662902 total: 37.7s remaining: 21s
655: learn: 0.2661980 total: 37.8s remaining: 21s
656: learn: 0.2661600 total: 37.8s remaining: 20.9s
657: learn: 0.2659662 total: 37.9s remaining: 20.8s
658: learn: 0.2656520 total: 37.9s remaining: 20.8s
659: learn: 0.2656081 total: 38s remaining: 20.7s
660: learn: 0.2654556 total: 38s remaining: 20.7s
661: learn: 0.2653668 total: 38.1s remaining: 20.6s
662: learn: 0.2653107 total: 38.1s remaining: 20.5s
663: learn: 0.2651168 total: 38.2s remaining: 20.5s
664: learn: 0.2650943 total: 38.2s remaining: 20.4s
665: learn: 0.2650483 total: 38.3s remaining: 20.4s
666: learn: 0.2649239 total: 38.3s remaining: 20.3s
667: learn: 0.2647924 total: 38.4s remaining: 20.2s
668: learn: 0.2646802 total: 38.4s remaining: 20.2s
669: learn: 0.2646279 total: 38.5s remaining: 20.1s
670: learn: 0.2645739 total: 38.5s remaining: 20s
671: learn: 0.2645522 total: 38.6s remaining: 20s
672: learn: 0.2644553 total: 38.6s remaining: 19.9s
673: learn: 0.2643095 total: 38.7s remaining: 19.9s
674: learn: 0.2642163 total: 38.8s remaining: 19.8s
675: learn: 0.2641665 total: 38.8s remaining: 19.7s
676: learn: 0.2640732 total: 38.9s remaining: 19.7s
677: learn: 0.2637663 total: 38.9s remaining: 19.6s
678: learn: 0.2637083 total: 39s remaining: 19.6s
679: learn: 0.2635982 total: 39s remaining: 19.5s
680: learn: 0.2635583 total: 39.1s remaining: 19.4s
681: learn: 0.2635406 total: 39.1s remaining: 19.4s
682: learn: 0.2634259 total: 39.2s remaining: 19.3s
683: learn: 0.2633410 total: 39.2s remaining: 19.3s
684: learn: 0.2633053 total: 39.3s remaining: 19.2s
685: learn: 0.2632727 total: 39.3s remaining: 19.1s
686: learn: 0.2632185 total: 39.4s remaining: 19.1s
687: learn: 0.2631015 total: 39.4s remaining: 19s
688: learn: 0.2630283 total: 39.5s remaining: 19s
689: learn: 0.2628803 total: 39.5s remaining: 18.9s
690: learn: 0.2626985 total: 39.6s remaining: 18.8s
691: learn: 0.2625979 total: 39.6s remaining: 18.8s
692: learn: 0.2625430 total: 39.7s remaining: 18.7s
693: learn: 0.2624232 total: 39.7s remaining: 18.7s
694: learn: 0.2622728 total: 39.8s remaining: 18.6s
695: learn: 0.2620818 total: 39.8s remaining: 18.5s
696: learn: 0.2620349 total: 39.9s remaining: 18.5s
697: learn: 0.2618882 total: 40s remaining: 18.4s
698: learn: 0.2618382 total: 40s remaining: 18.4s
699: learn: 0.2616821 total: 40.1s remaining: 18.3s
700: learn: 0.2616391 total: 40.2s remaining: 18.3s
701: learn: 0.2615845 total: 40.2s remaining: 18.2s
702: learn: 0.2615334 total: 40.3s remaining: 18.2s
703: learn: 0.2613887 total: 40.3s remaining: 18.1s
704: learn: 0.2611156 total: 40.4s remaining: 18.1s
705: learn: 0.2610441 total: 40.5s remaining: 18s
706: learn: 0.2609959 total: 40.5s remaining: 17.9s
707: learn: 0.2608672 total: 40.6s remaining: 17.9s
708: learn: 0.2607493 total: 40.7s remaining: 17.8s
709: learn: 0.2607201 total: 40.7s remaining: 17.8s
710: learn: 0.2605487 total: 40.8s remaining: 17.7s
711: learn: 0.2604042 total: 40.9s remaining: 17.7s
712: learn: 0.2604039 total: 40.9s remaining: 17.6s
713: learn: 0.2603416 total: 40.9s remaining: 17.5s
714: learn: 0.2602386 total: 41s remaining: 17.5s
715: learn: 0.2600764 total: 41.1s remaining: 17.4s
716: learn: 0.2599958 total: 41.1s remaining: 17.4s
717: learn: 0.2597771 total: 41.2s remaining: 17.3s
718: learn: 0.2597572 total: 41.2s remaining: 17.3s
719: learn: 0.2596510 total: 41.3s remaining: 17.2s
720: learn: 0.2596063 total: 41.4s remaining: 17.2s
721: learn: 0.2595767 total: 41.4s remaining: 17.1s
722: learn: 0.2594698 total: 41.5s remaining: 17s
723: learn: 0.2594150 total: 41.5s remaining: 17s
724: learn: 0.2593818 total: 41.6s remaining: 16.9s
725: learn: 0.2593371 total: 41.7s remaining: 16.9s
726: learn: 0.2593078 total: 41.7s remaining: 16.8s
727: learn: 0.2592292 total: 41.8s remaining: 16.8s
728: learn: 0.2590583 total: 41.9s remaining: 16.7s
729: learn: 0.2588513 total: 41.9s remaining: 16.7s
730: learn: 0.2587462 total: 42s remaining: 16.6s
731: learn: 0.2586050 total: 42s remaining: 16.5s
732: learn: 0.2584774 total: 42.1s remaining: 16.5s
733: learn: 0.2583982 total: 42.2s remaining: 16.4s
734: learn: 0.2582888 total: 42.2s remaining: 16.4s
735: learn: 0.2582579 total: 42.3s remaining: 16.3s
736: learn: 0.2581831 total: 42.3s remaining: 16.3s
737: learn: 0.2579958 total: 42.4s remaining: 16.2s
738: learn: 0.2579256 total: 42.5s remaining: 16.1s
739: learn: 0.2578963 total: 42.5s remaining: 16.1s
740: learn: 0.2578518 total: 42.6s remaining: 16s
741: learn: 0.2577735 total: 42.6s remaining: 16s
742: learn: 0.2577601 total: 42.7s remaining: 15.9s
743: learn: 0.2577354 total: 42.8s remaining: 15.9s
744: learn: 0.2576980 total: 42.8s remaining: 15.8s
745: learn: 0.2576777 total: 42.9s remaining: 15.8s
746: learn: 0.2575589 total: 43s remaining: 15.7s
747: learn: 0.2574414 total: 43s remaining: 15.6s
748: learn: 0.2571850 total: 43.1s remaining: 15.6s
749: learn: 0.2571519 total: 43.1s remaining: 15.5s
750: learn: 0.2571002 total: 43.2s remaining: 15.5s
751: learn: 0.2569834 total: 43.2s remaining: 15.4s
752: learn: 0.2569308 total: 43.3s remaining: 15.4s
753: learn: 0.2568929 total: 43.4s remaining: 15.3s
754: learn: 0.2567667 total: 43.4s remaining: 15.2s
755: learn: 0.2567247 total: 43.4s remaining: 15.2s
756: learn: 0.2566305 total: 43.5s remaining: 15.1s
757: learn: 0.2566084 total: 43.6s remaining: 15.1s
758: learn: 0.2566046 total: 43.6s remaining: 15s
759: learn: 0.2565761 total: 43.6s remaining: 14.9s
760: learn: 0.2565494 total: 43.7s remaining: 14.9s
761: learn: 0.2565366 total: 43.8s remaining: 14.8s
762: learn: 0.2563836 total: 43.8s remaining: 14.8s
763: learn: 0.2562476 total: 43.9s remaining: 14.7s
764: learn: 0.2560954 total: 43.9s remaining: 14.6s
765: learn: 0.2558844 total: 44s remaining: 14.6s
766: learn: 0.2557436 total: 44s remaining: 14.5s
767: learn: 0.2557085 total: 44.1s remaining: 14.5s
768: learn: 0.2557041 total: 44.1s remaining: 14.4s
769: learn: 0.2556929 total: 44.2s remaining: 14.3s
770: learn: 0.2556380 total: 44.2s remaining: 14.3s
771: learn: 0.2555292 total: 44.3s remaining: 14.2s
772: learn: 0.2554501 total: 44.3s remaining: 14.2s
773: learn: 0.2554084 total: 44.4s remaining: 14.1s
774: learn: 0.2553149 total: 44.4s remaining: 14s
775: learn: 0.2551356 total: 44.5s remaining: 14s
776: learn: 0.2551066 total: 44.5s remaining: 13.9s
777: learn: 0.2549291 total: 44.6s remaining: 13.9s
778: learn: 0.2548842 total: 44.6s remaining: 13.8s
779: learn: 0.2548055 total: 44.7s remaining: 13.7s
780: learn: 0.2547608 total: 44.7s remaining: 13.7s
781: learn: 0.2546920 total: 44.8s remaining: 13.6s
782: learn: 0.2546425 total: 44.8s remaining: 13.6s
783: learn: 0.2545870 total: 44.9s remaining: 13.5s
784: learn: 0.2545408 total: 44.9s remaining: 13.4s
785: learn: 0.2544838 total: 45s remaining: 13.4s
786: learn: 0.2543660 total: 45s remaining: 13.3s
787: learn: 0.2543432 total: 45.1s remaining: 13.3s
788: learn: 0.2542576 total: 45.1s remaining: 13.2s
789: learn: 0.2541733 total: 45.2s remaining: 13.1s
790: learn: 0.2541090 total: 45.2s remaining: 13.1s
791: learn: 0.2540417 total: 45.3s remaining: 13s
792: learn: 0.2539916 total: 45.3s remaining: 13s
793: learn: 0.2539677 total: 45.4s remaining: 12.9s
794: learn: 0.2539428 total: 45.4s remaining: 12.9s
795: learn: 0.2539042 total: 45.5s remaining: 12.8s
796: learn: 0.2538576 total: 45.5s remaining: 12.7s
797: learn: 0.2537701 total: 45.6s remaining: 12.7s
798: learn: 0.2537115 total: 45.6s remaining: 12.6s
799: learn: 0.2536481 total: 45.7s remaining: 12.6s
800: learn: 0.2536228 total: 45.7s remaining: 12.5s
801: learn: 0.2535727 total: 45.8s remaining: 12.4s
802: learn: 0.2535487 total: 45.8s remaining: 12.4s
803: learn: 0.2534952 total: 45.9s remaining: 12.3s
804: learn: 0.2534493 total: 45.9s remaining: 12.3s
805: learn: 0.2533761 total: 46s remaining: 12.2s
806: learn: 0.2532466 total: 46s remaining: 12.1s
807: learn: 0.2532462 total: 46s remaining: 12.1s
808: learn: 0.2532067 total: 46.1s remaining: 12s
809: learn: 0.2531464 total: 46.2s remaining: 12s
810: learn: 0.2530943 total: 46.2s remaining: 11.9s
811: learn: 0.2530050 total: 46.3s remaining: 11.8s
812: learn: 0.2529708 total: 46.3s remaining: 11.8s
813: learn: 0.2527570 total: 46.4s remaining: 11.7s
814: learn: 0.2526710 total: 46.4s remaining: 11.7s
815: learn: 0.2526415 total: 46.5s remaining: 11.6s
816: learn: 0.2526085 total: 46.5s remaining: 11.6s
817: learn: 0.2525443 total: 46.6s remaining: 11.5s
818: learn: 0.2525241 total: 46.6s remaining: 11.4s
819: learn: 0.2524576 total: 46.7s remaining: 11.4s
820: learn: 0.2523306 total: 46.8s remaining: 11.3s
821: learn: 0.2523016 total: 46.8s remaining: 11.3s
822: learn: 0.2522631 total: 46.9s remaining: 11.2s
823: learn: 0.2521735 total: 47s remaining: 11.2s
824: learn: 0.2520613 total: 47s remaining: 11.1s
825: learn: 0.2520009 total: 47.1s remaining: 11.1s
826: learn: 0.2520009 total: 47.1s remaining: 11s
827: learn: 0.2518800 total: 47.2s remaining: 10.9s
828: learn: 0.2518335 total: 47.3s remaining: 10.9s
829: learn: 0.2517177 total: 47.3s remaining: 10.8s
830: learn: 0.2516732 total: 47.4s remaining: 10.8s
831: learn: 0.2514295 total: 47.4s remaining: 10.7s
832: learn: 0.2513960 total: 47.5s remaining: 10.7s
833: learn: 0.2513073 total: 47.6s remaining: 10.6s
834: learn: 0.2512218 total: 47.6s remaining: 10.6s
835: learn: 0.2512085 total: 47.7s remaining: 10.5s
836: learn: 0.2511296 total: 47.8s remaining: 10.4s
837: learn: 0.2510901 total: 47.8s remaining: 10.4s
838: learn: 0.2510439 total: 47.9s remaining: 10.3s
839: learn: 0.2509830 total: 47.9s remaining: 10.3s
840: learn: 0.2508350 total: 48s remaining: 10.2s
841: learn: 0.2507509 total: 48.1s remaining: 10.2s
842: learn: 0.2507309 total: 48.1s remaining: 10.1s
843: learn: 0.2506659 total: 48.2s remaining: 10s
844: learn: 0.2505674 total: 48.3s remaining: 9.99s
845: learn: 0.2505150 total: 48.3s remaining: 9.94s
846: learn: 0.2504684 total: 48.4s remaining: 9.89s
847: learn: 0.2504249 total: 48.5s remaining: 9.83s
848: learn: 0.2503773 total: 48.5s remaining: 9.78s
849: learn: 0.2503398 total: 48.6s remaining: 9.72s
850: learn: 0.2503212 total: 48.7s remaining: 9.66s
851: learn: 0.2502323 total: 48.7s remaining: 9.61s
852: learn: 0.2501246 total: 48.8s remaining: 9.55s
853: learn: 0.2500718 total: 48.9s remaining: 9.5s
854: learn: 0.2500342 total: 48.9s remaining: 9.44s
855: learn: 0.2499886 total: 49s remaining: 9.39s
856: learn: 0.2499479 total: 49.1s remaining: 9.33s
857: learn: 0.2499360 total: 49.1s remaining: 9.28s
858: learn: 0.2499057 total: 49.2s remaining: 9.22s
859: learn: 0.2498744 total: 49.3s remaining: 9.17s
860: learn: 0.2498365 total: 49.3s remaining: 9.11s
861: learn: 0.2497244 total: 49.4s remaining: 9.05s
862: learn: 0.2497043 total: 49.5s remaining: 9s
863: learn: 0.2496797 total: 49.5s remaining: 8.94s
864: learn: 0.2495789 total: 49.6s remaining: 8.89s
865: learn: 0.2495507 total: 49.7s remaining: 8.83s
866: learn: 0.2494854 total: 49.7s remaining: 8.78s
867: learn: 0.2493963 total: 49.8s remaining: 8.72s
868: learn: 0.2493166 total: 49.9s remaining: 8.66s
869: learn: 0.2492590 total: 49.9s remaining: 8.61s
870: learn: 0.2492396 total: 50s remaining: 8.55s
871: learn: 0.2492186 total: 50.1s remaining: 8.5s
872: learn: 0.2491617 total: 50.1s remaining: 8.44s
873: learn: 0.2490435 total: 50.2s remaining: 8.38s
874: learn: 0.2489518 total: 50.2s remaining: 8.32s
875: learn: 0.2488663 total: 50.3s remaining: 8.27s
876: learn: 0.2486644 total: 50.3s remaining: 8.21s
877: learn: 0.2486257 total: 50.4s remaining: 8.15s
878: learn: 0.2483930 total: 50.5s remaining: 8.09s
879: learn: 0.2482275 total: 50.5s remaining: 8.04s
880: learn: 0.2481654 total: 50.6s remaining: 7.98s
881: learn: 0.2481345 total: 50.6s remaining: 7.92s
882: learn: 0.2480914 total: 50.7s remaining: 7.86s
883: learn: 0.2479906 total: 50.7s remaining: 7.81s
884: learn: 0.2479036 total: 50.8s remaining: 7.75s
885: learn: 0.2478508 total: 50.9s remaining: 7.69s
886: learn: 0.2477200 total: 50.9s remaining: 7.64s
887: learn: 0.2476738 total: 51s remaining: 7.58s
888: learn: 0.2476586 total: 51s remaining: 7.52s
889: learn: 0.2476323 total: 51.1s remaining: 7.46s
890: learn: 0.2475949 total: 51.1s remaining: 7.4s
891: learn: 0.2475124 total: 51.2s remaining: 7.35s
892: learn: 0.2474638 total: 51.3s remaining: 7.29s
893: learn: 0.2474571 total: 51.3s remaining: 7.23s
894: learn: 0.2473920 total: 51.4s remaining: 7.17s
895: learn: 0.2473561 total: 51.4s remaining: 7.12s
896: learn: 0.2472793 total: 51.5s remaining: 7.06s
897: learn: 0.2471488 total: 51.5s remaining: 7s
898: learn: 0.2470772 total: 51.6s remaining: 6.94s
899: learn: 0.2469985 total: 51.6s remaining: 6.88s
900: learn: 0.2469209 total: 51.7s remaining: 6.83s
901: learn: 0.2468911 total: 51.8s remaining: 6.77s
902: learn: 0.2468783 total: 51.8s remaining: 6.71s
903: learn: 0.2468471 total: 51.9s remaining: 6.65s
904: learn: 0.2468089 total: 51.9s remaining: 6.6s
905: learn: 0.2466596 total: 52s remaining: 6.54s
906: learn: 0.2466032 total: 52s remaining: 6.48s
907: learn: 0.2465911 total: 52.1s remaining: 6.42s
908: learn: 0.2464889 total: 52.1s remaining: 6.36s
909: learn: 0.2464884 total: 52.2s remaining: 6.3s
910: learn: 0.2464571 total: 52.2s remaining: 6.25s
911: learn: 0.2463539 total: 52.3s remaining: 6.19s
912: learn: 0.2462823 total: 52.3s remaining: 6.13s
913: learn: 0.2462650 total: 52.4s remaining: 6.08s
914: learn: 0.2462591 total: 52.4s remaining: 6.02s
915: learn: 0.2461984 total: 52.5s remaining: 5.96s
916: learn: 0.2461484 total: 52.6s remaining: 5.9s
917: learn: 0.2460946 total: 52.6s remaining: 5.85s
918: learn: 0.2459605 total: 52.7s remaining: 5.79s
919: learn: 0.2459401 total: 52.7s remaining: 5.73s
920: learn: 0.2459182 total: 52.8s remaining: 5.67s
921: learn: 0.2458711 total: 52.8s remaining: 5.62s
922: learn: 0.2457945 total: 52.9s remaining: 5.56s
923: learn: 0.2457806 total: 52.9s remaining: 5.5s
924: learn: 0.2456691 total: 53s remaining: 5.44s
925: learn: 0.2456215 total: 53.1s remaining: 5.38s
926: learn: 0.2455809 total: 53.1s remaining: 5.33s
927: learn: 0.2454567 total: 53.2s remaining: 5.27s
928: learn: 0.2454192 total: 53.2s remaining: 5.21s
929: learn: 0.2453560 total: 53.3s remaining: 5.16s
930: learn: 0.2453149 total: 53.3s remaining: 5.1s
931: learn: 0.2452592 total: 53.4s remaining: 5.04s
932: learn: 0.2451994 total: 53.5s remaining: 4.98s
933: learn: 0.2451678 total: 53.5s remaining: 4.93s
934: learn: 0.2450798 total: 53.6s remaining: 4.87s
935: learn: 0.2450381 total: 53.7s remaining: 4.82s
936: learn: 0.2450259 total: 53.7s remaining: 4.76s
937: learn: 0.2449836 total: 53.8s remaining: 4.7s
938: learn: 0.2449505 total: 53.9s remaining: 4.64s
939: learn: 0.2448741 total: 53.9s remaining: 4.59s
940: learn: 0.2448513 total: 54s remaining: 4.53s
941: learn: 0.2448225 total: 54.1s remaining: 4.48s
942: learn: 0.2448170 total: 54.1s remaining: 4.42s
943: learn: 0.2447392 total: 54.2s remaining: 4.36s
944: learn: 0.2446966 total: 54.2s remaining: 4.3s
945: learn: 0.2446649 total: 54.3s remaining: 4.25s
946: learn: 0.2446516 total: 54.4s remaining: 4.19s
947: learn: 0.2445913 total: 54.4s remaining: 4.13s
948: learn: 0.2445723 total: 54.5s remaining: 4.08s
949: learn: 0.2445723 total: 54.5s remaining: 4.02s
950: learn: 0.2445045 total: 54.6s remaining: 3.96s
951: learn: 0.2444948 total: 54.6s remaining: 3.9s
952: learn: 0.2444885 total: 54.7s remaining: 3.85s
953: learn: 0.2444613 total: 54.8s remaining: 3.79s
954: learn: 0.2444115 total: 54.9s remaining: 3.73s
955: learn: 0.2443528 total: 54.9s remaining: 3.68s
956: learn: 0.2443522 total: 55s remaining: 3.62s
957: learn: 0.2443263 total: 55s remaining: 3.56s
958: learn: 0.2443258 total: 55.1s remaining: 3.5s
959: learn: 0.2443256 total: 55.1s remaining: 3.44s
960: learn: 0.2442948 total: 55.2s remaining: 3.39s
961: learn: 0.2442566 total: 55.3s remaining: 3.33s
962: learn: 0.2442541 total: 55.3s remaining: 3.27s
963: learn: 0.2442225 total: 55.4s remaining: 3.22s
964: learn: 0.2441932 total: 55.4s remaining: 3.16s
965: learn: 0.2441237 total: 55.5s remaining: 3.1s
966: learn: 0.2440794 total: 55.6s remaining: 3.04s
967: learn: 0.2440361 total: 55.6s remaining: 2.99s
968: learn: 0.2440355 total: 55.7s remaining: 2.93s
969: learn: 0.2439808 total: 55.7s remaining: 2.87s
970: learn: 0.2439228 total: 55.8s remaining: 2.81s
971: learn: 0.2438556 total: 55.9s remaining: 2.76s
972: learn: 0.2438470 total: 55.9s remaining: 2.7s
973: learn: 0.2437253 total: 56s remaining: 2.64s
974: learn: 0.2436871 total: 56s remaining: 2.58s
975: learn: 0.2436306 total: 56.1s remaining: 2.53s
976: learn: 0.2436045 total: 56.2s remaining: 2.47s
977: learn: 0.2435697 total: 56.2s remaining: 2.41s
978: learn: 0.2435281 total: 56.3s remaining: 2.36s
979: learn: 0.2434822 total: 56.3s remaining: 2.3s
980: learn: 0.2433903 total: 56.4s remaining: 2.24s
981: learn: 0.2433468 total: 56.5s remaining: 2.19s
982: learn: 0.2432790 total: 56.5s remaining: 2.13s
983: learn: 0.2432357 total: 56.6s remaining: 2.07s
984: learn: 0.2432334 total: 56.7s remaining: 2.01s
985: learn: 0.2431122 total: 56.8s remaining: 1.96s
986: learn: 0.2430851 total: 56.8s remaining: 1.9s
987: learn: 0.2430789 total: 56.9s remaining: 1.84s
988: learn: 0.2430583 total: 56.9s remaining: 1.78s
989: learn: 0.2430578 total: 57s remaining: 1.73s
990: learn: 0.2430244 total: 57s remaining: 1.67s
991: learn: 0.2430047 total: 57.1s remaining: 1.61s
992: learn: 0.2429617 total: 57.1s remaining: 1.55s
993: learn: 0.2429155 total: 57.2s remaining: 1.5s
994: learn: 0.2428904 total: 57.2s remaining: 1.44s
995: learn: 0.2428570 total: 57.3s remaining: 1.38s
996: learn: 0.2427981 total: 57.3s remaining: 1.32s
997: learn: 0.2427755 total: 57.4s remaining: 1.26s
998: learn: 0.2427220 total: 57.4s remaining: 1.21s
999: learn: 0.2426342 total: 57.5s remaining: 1.15s
1000: learn: 0.2425716 total: 57.5s remaining: 1.09s
1001: learn: 0.2425471 total: 57.6s remaining: 1.03s
1002: learn: 0.2424850 total: 57.6s remaining: 977ms
1003: learn: 0.2424068 total: 57.7s remaining: 919ms
1004: learn: 0.2423372 total: 57.7s remaining: 862ms
1005: learn: 0.2423136 total: 57.8s remaining: 804ms
1006: learn: 0.2422968 total: 57.9s remaining: 747ms
1007: learn: 0.2422628 total: 57.9s remaining: 689ms
1008: learn: 0.2422449 total: 58s remaining: 632ms
1009: learn: 0.2422380 total: 58s remaining: 574ms
1010: learn: 0.2422291 total: 58.1s remaining: 517ms
1011: learn: 0.2422118 total: 58.1s remaining: 459ms
1012: learn: 0.2421985 total: 58.1s remaining: 402ms
1013: learn: 0.2421677 total: 58.2s remaining: 344ms
1014: learn: 0.2421669 total: 58.2s remaining: 287ms
1015: learn: 0.2421511 total: 58.3s remaining: 229ms
1016: learn: 0.2420978 total: 58.3s remaining: 172ms
1017: learn: 0.2420560 total: 58.4s remaining: 115ms
1018: learn: 0.2419674 total: 58.4s remaining: 57.4ms
1019: learn: 0.2419285 total: 58.5s remaining: 0us
Finished training fold 6 - running score 0.8637186720135708
Finished training 7 models
3530
In [72]:
sns.set_color_codes("muted")
sns.barplot(x='Accuracy', y='Classifier', data=log, color='g')
plt.xlabel('Accuracy %')
plt.title('Classifier Accuracy');
In [81]:
stack_train.to_csv(f'{PATH}\\AV_Stud_2\\stack_train.csv', index = False)
stack_test.to_csv(f'{PATH}\\AV_Stud_2\\stack_test.csv', index = False)
log.to_csv(f'{PATH}\\AV_Stud_2\\log.csv', index = False)
In [77]:
model_xgb, p_train, p_test = mlcrate.xgb.train_kfold(params, X_stack_train, target, X_stack_test\
, folds = 7,skip_checks = True, stratify=target, print_imp='final')
name = model_xgb[3].__class__.__name__
stack_test[name] = p_test
stack_train[name] = p_train
In [78]:
_, _, p_test = mlcrate.xgb.train_kfold(params, stack_train, target, stack_test\
, folds = 7,skip_checks = True, stratify=target, print_imp='final')
[mlcrate] Training 7 stratified XGBoost models on training set (18359, 10) with test set (15021, 10)
[mlcrate] Running fold 0, 15735 train samples, 2624 validation samples
[0] train-auc:0.615934 valid-auc:0.607321
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.629118 valid-auc:0.628424
[2] train-auc:0.630865 valid-auc:0.633996
[3] train-auc:0.630775 valid-auc:0.63441
[4] train-auc:0.637561 valid-auc:0.642621
[5] train-auc:0.644279 valid-auc:0.651041
[6] train-auc:0.64541 valid-auc:0.652507
[7] train-auc:0.645342 valid-auc:0.65265
[8] train-auc:0.645266 valid-auc:0.652513
[9] train-auc:0.646424 valid-auc:0.651394
[10] train-auc:0.646405 valid-auc:0.651458
[11] train-auc:0.646484 valid-auc:0.650984
[12] train-auc:0.646599 valid-auc:0.650187
[13] train-auc:0.650218 valid-auc:0.658353
[14] train-auc:0.650199 valid-auc:0.658422
[15] train-auc:0.650164 valid-auc:0.658099
[16] train-auc:0.650391 valid-auc:0.658565
[17] train-auc:0.650478 valid-auc:0.658482
[18] train-auc:0.650623 valid-auc:0.658277
[19] train-auc:0.650668 valid-auc:0.65829
[20] train-auc:0.650622 valid-auc:0.658392
[21] train-auc:0.655048 valid-auc:0.662507
[22] train-auc:0.655052 valid-auc:0.662585
[23] train-auc:0.655085 valid-auc:0.662303
[24] train-auc:0.655142 valid-auc:0.662414
[25] train-auc:0.655304 valid-auc:0.662048
[26] train-auc:0.655819 valid-auc:0.661765
[27] train-auc:0.660833 valid-auc:0.663968
[28] train-auc:0.661691 valid-auc:0.664949
[29] train-auc:0.661688 valid-auc:0.664999
[30] train-auc:0.661662 valid-auc:0.664861
[31] train-auc:0.66186 valid-auc:0.665312
[32] train-auc:0.66207 valid-auc:0.664969
[33] train-auc:0.662091 valid-auc:0.664901
[34] train-auc:0.662253 valid-auc:0.665056
[35] train-auc:0.662816 valid-auc:0.665105
[36] train-auc:0.663502 valid-auc:0.665257
[37] train-auc:0.670213 valid-auc:0.669651
[38] train-auc:0.670422 valid-auc:0.669924
[39] train-auc:0.670559 valid-auc:0.669817
[40] train-auc:0.671099 valid-auc:0.669842
[41] train-auc:0.671199 valid-auc:0.669926
[42] train-auc:0.671195 valid-auc:0.669678
[43] train-auc:0.67153 valid-auc:0.669751
[44] train-auc:0.671778 valid-auc:0.669314
[45] train-auc:0.676661 valid-auc:0.671258
[46] train-auc:0.676841 valid-auc:0.671575
[47] train-auc:0.676907 valid-auc:0.671537
[48] train-auc:0.676876 valid-auc:0.671589
[49] train-auc:0.677141 valid-auc:0.671784
[50] train-auc:0.677378 valid-auc:0.671657
[51] train-auc:0.677713 valid-auc:0.671443
[52] train-auc:0.678885 valid-auc:0.670536
[53] train-auc:0.6788 valid-auc:0.670651
[54] train-auc:0.678847 valid-auc:0.670599
[55] train-auc:0.680895 valid-auc:0.674062
[56] train-auc:0.681812 valid-auc:0.67389
[57] train-auc:0.681611 valid-auc:0.673196
[58] train-auc:0.681898 valid-auc:0.673271
[59] train-auc:0.683113 valid-auc:0.673194
[60] train-auc:0.683214 valid-auc:0.673399
[61] train-auc:0.683867 valid-auc:0.673225
[62] train-auc:0.684356 valid-auc:0.673472
[63] train-auc:0.684677 valid-auc:0.673257
[64] train-auc:0.685092 valid-auc:0.673717
[65] train-auc:0.685576 valid-auc:0.673682
[66] train-auc:0.686103 valid-auc:0.673669
[67] train-auc:0.686657 valid-auc:0.673444
[68] train-auc:0.688908 valid-auc:0.672324
[69] train-auc:0.689481 valid-auc:0.672534
[70] train-auc:0.690426 valid-auc:0.672654
[71] train-auc:0.690326 valid-auc:0.672765
[72] train-auc:0.694816 valid-auc:0.671228
[73] train-auc:0.698453 valid-auc:0.674534
[74] train-auc:0.698581 valid-auc:0.674835
[75] train-auc:0.700187 valid-auc:0.673634
[76] train-auc:0.700177 valid-auc:0.673875
[77] train-auc:0.701134 valid-auc:0.674674
[78] train-auc:0.702324 valid-auc:0.673849
[79] train-auc:0.703231 valid-auc:0.673757
[80] train-auc:0.703574 valid-auc:0.673356
[81] train-auc:0.703767 valid-auc:0.673388
[82] train-auc:0.704577 valid-auc:0.67077
[83] train-auc:0.705654 valid-auc:0.671271
[84] train-auc:0.705672 valid-auc:0.671519
[85] train-auc:0.708169 valid-auc:0.673153
[86] train-auc:0.707973 valid-auc:0.67291
[87] train-auc:0.708581 valid-auc:0.673412
[88] train-auc:0.709037 valid-auc:0.673354
[89] train-auc:0.709048 valid-auc:0.673106
[90] train-auc:0.709811 valid-auc:0.671929
[91] train-auc:0.710282 valid-auc:0.672744
[92] train-auc:0.710329 valid-auc:0.672786
[93] train-auc:0.710719 valid-auc:0.673116
[94] train-auc:0.712233 valid-auc:0.672916
[95] train-auc:0.713171 valid-auc:0.673695
[96] train-auc:0.713714 valid-auc:0.673221
[97] train-auc:0.713787 valid-auc:0.673067
[98] train-auc:0.714316 valid-auc:0.673016
[99] train-auc:0.716689 valid-auc:0.671455
[100] train-auc:0.719782 valid-auc:0.673147
[101] train-auc:0.720049 valid-auc:0.672066
[102] train-auc:0.719563 valid-auc:0.672066
[103] train-auc:0.720396 valid-auc:0.671119
[104] train-auc:0.720777 valid-auc:0.670814
[105] train-auc:0.720904 valid-auc:0.670678
[106] train-auc:0.720963 valid-auc:0.670695
[107] train-auc:0.722829 valid-auc:0.670524
[108] train-auc:0.72253 valid-auc:0.670846
[109] train-auc:0.723734 valid-auc:0.671401
[110] train-auc:0.724532 valid-auc:0.671035
[111] train-auc:0.725308 valid-auc:0.670546
[112] train-auc:0.726317 valid-auc:0.670556
[113] train-auc:0.726746 valid-auc:0.671579
[114] train-auc:0.726607 valid-auc:0.671398
[115] train-auc:0.72746 valid-auc:0.671656
[116] train-auc:0.72808 valid-auc:0.671582
[117] train-auc:0.728219 valid-auc:0.671652
[118] train-auc:0.728726 valid-auc:0.67157
[119] train-auc:0.728726 valid-auc:0.67157
[120] train-auc:0.730151 valid-auc:0.671046
[121] train-auc:0.730184 valid-auc:0.671281
[122] train-auc:0.730207 valid-auc:0.671496
[123] train-auc:0.730646 valid-auc:0.671289
[124] train-auc:0.731916 valid-auc:0.672034
Stopping. Best iteration:
[74] train-auc:0.698581 valid-auc:0.674835
C:\ProgramData\Anaconda3\lib\site-packages\mlcrate\backend.py:7: UserWarning: Timer.format_elapsed() has been deprecated in favour of Timer.fsince() and will be removed soon
warn(message)
[mlcrate] Finished training fold 0 - took 4s - running score 0.674835
[mlcrate] Running fold 1, 15735 train samples, 2624 validation samples
[0] train-auc:0.628639 valid-auc:0.648939
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.628639 valid-auc:0.648939
[2] train-auc:0.628639 valid-auc:0.648939
[3] train-auc:0.639463 valid-auc:0.667051
[4] train-auc:0.639412 valid-auc:0.666863
[5] train-auc:0.639371 valid-auc:0.666893
[6] train-auc:0.639371 valid-auc:0.666893
[7] train-auc:0.641499 valid-auc:0.67121
[8] train-auc:0.643775 valid-auc:0.674814
[9] train-auc:0.645027 valid-auc:0.678509
[10] train-auc:0.644915 valid-auc:0.678063
[11] train-auc:0.644915 valid-auc:0.678063
[12] train-auc:0.644915 valid-auc:0.678063
[13] train-auc:0.644915 valid-auc:0.678063
[14] train-auc:0.645869 valid-auc:0.680225
[15] train-auc:0.647503 valid-auc:0.682732
[16] train-auc:0.647628 valid-auc:0.682788
[17] train-auc:0.650234 valid-auc:0.6822
[18] train-auc:0.650376 valid-auc:0.682545
[19] train-auc:0.659359 valid-auc:0.683177
[20] train-auc:0.659335 valid-auc:0.683361
[21] train-auc:0.659312 valid-auc:0.683374
[22] train-auc:0.65959 valid-auc:0.683207
[23] train-auc:0.659568 valid-auc:0.683362
[24] train-auc:0.660001 valid-auc:0.682689
[25] train-auc:0.660143 valid-auc:0.68271
[26] train-auc:0.660125 valid-auc:0.68272
[27] train-auc:0.660185 valid-auc:0.682759
[28] train-auc:0.660129 valid-auc:0.682824
[29] train-auc:0.660165 valid-auc:0.683293
[30] train-auc:0.660587 valid-auc:0.684112
[31] train-auc:0.660761 valid-auc:0.684187
[32] train-auc:0.660848 valid-auc:0.684263
[33] train-auc:0.664261 valid-auc:0.686543
[34] train-auc:0.664488 valid-auc:0.686667
[35] train-auc:0.664856 valid-auc:0.687662
[36] train-auc:0.664906 valid-auc:0.687438
[37] train-auc:0.665274 valid-auc:0.687415
[38] train-auc:0.66551 valid-auc:0.68765
[39] train-auc:0.665676 valid-auc:0.687647
[40] train-auc:0.665628 valid-auc:0.687401
[41] train-auc:0.665618 valid-auc:0.687766
[42] train-auc:0.665654 valid-auc:0.687737
[43] train-auc:0.666395 valid-auc:0.688237
[44] train-auc:0.666367 valid-auc:0.688224
[45] train-auc:0.666923 valid-auc:0.688035
[46] train-auc:0.667256 valid-auc:0.688167
[47] train-auc:0.671859 valid-auc:0.692352
[48] train-auc:0.672296 valid-auc:0.692311
[49] train-auc:0.672566 valid-auc:0.692371
[50] train-auc:0.673342 valid-auc:0.692231
[51] train-auc:0.672699 valid-auc:0.696651
[52] train-auc:0.673318 valid-auc:0.696472
[53] train-auc:0.677211 valid-auc:0.698064
[54] train-auc:0.677436 valid-auc:0.697359
[55] train-auc:0.677876 valid-auc:0.697179
[56] train-auc:0.677862 valid-auc:0.697663
[57] train-auc:0.681376 valid-auc:0.695814
[58] train-auc:0.682089 valid-auc:0.695921
[59] train-auc:0.683711 valid-auc:0.695758
[60] train-auc:0.683685 valid-auc:0.69593
[61] train-auc:0.683551 valid-auc:0.695964
[62] train-auc:0.683604 valid-auc:0.695886
[63] train-auc:0.683866 valid-auc:0.695557
[64] train-auc:0.684454 valid-auc:0.695554
[65] train-auc:0.68573 valid-auc:0.69579
[66] train-auc:0.685882 valid-auc:0.69616
[67] train-auc:0.686593 valid-auc:0.696494
[68] train-auc:0.68694 valid-auc:0.696419
[69] train-auc:0.687531 valid-auc:0.69686
[70] train-auc:0.688697 valid-auc:0.696372
[71] train-auc:0.688587 valid-auc:0.697077
[72] train-auc:0.688833 valid-auc:0.696783
[73] train-auc:0.689049 valid-auc:0.696427
[74] train-auc:0.689711 valid-auc:0.695958
[75] train-auc:0.690355 valid-auc:0.69535
[76] train-auc:0.690844 valid-auc:0.695395
[77] train-auc:0.69135 valid-auc:0.695268
[78] train-auc:0.692021 valid-auc:0.6953
[79] train-auc:0.692763 valid-auc:0.694945
[80] train-auc:0.693638 valid-auc:0.695118
[81] train-auc:0.696377 valid-auc:0.695219
[82] train-auc:0.701455 valid-auc:0.695041
[83] train-auc:0.702063 valid-auc:0.695364
[84] train-auc:0.704282 valid-auc:0.695211
[85] train-auc:0.704026 valid-auc:0.69535
[86] train-auc:0.70491 valid-auc:0.695253
[87] train-auc:0.705838 valid-auc:0.694785
[88] train-auc:0.709137 valid-auc:0.696096
[89] train-auc:0.709083 valid-auc:0.695762
[90] train-auc:0.709256 valid-auc:0.695442
[91] train-auc:0.710596 valid-auc:0.695431
[92] train-auc:0.711459 valid-auc:0.696167
[93] train-auc:0.711753 valid-auc:0.696677
[94] train-auc:0.711789 valid-auc:0.696942
[95] train-auc:0.712766 valid-auc:0.697433
[96] train-auc:0.714276 valid-auc:0.697433
[97] train-auc:0.715478 valid-auc:0.697179
[98] train-auc:0.716676 valid-auc:0.696317
[99] train-auc:0.716517 valid-auc:0.696086
[100] train-auc:0.717299 valid-auc:0.694772
[101] train-auc:0.718754 valid-auc:0.694277
[102] train-auc:0.720401 valid-auc:0.694116
[103] train-auc:0.720608 valid-auc:0.693969
Stopping. Best iteration:
[53] train-auc:0.677211 valid-auc:0.698064
[mlcrate] Finished training fold 1 - took 3s - running score 0.6864494999999999
[mlcrate] Running fold 2, 15736 train samples, 2623 validation samples
[0] train-auc:0.614738 valid-auc:0.618443
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.628113 valid-auc:0.638768
[2] train-auc:0.642242 valid-auc:0.657341
[3] train-auc:0.642606 valid-auc:0.657806
[4] train-auc:0.64376 valid-auc:0.659641
[5] train-auc:0.646498 valid-auc:0.664198
[6] train-auc:0.646328 valid-auc:0.66697
[7] train-auc:0.646363 valid-auc:0.667055
[8] train-auc:0.646394 valid-auc:0.667149
[9] train-auc:0.648106 valid-auc:0.667954
[10] train-auc:0.648044 valid-auc:0.668096
[11] train-auc:0.648017 valid-auc:0.66801
[12] train-auc:0.648002 valid-auc:0.667806
[13] train-auc:0.647874 valid-auc:0.667578
[14] train-auc:0.649595 valid-auc:0.667503
[15] train-auc:0.649605 valid-auc:0.667556
[16] train-auc:0.649702 valid-auc:0.667578
[17] train-auc:0.659053 valid-auc:0.676179
[18] train-auc:0.659076 valid-auc:0.67615
[19] train-auc:0.659042 valid-auc:0.676183
[20] train-auc:0.664538 valid-auc:0.680528
[21] train-auc:0.664761 valid-auc:0.680674
[22] train-auc:0.664782 valid-auc:0.680639
[23] train-auc:0.664866 valid-auc:0.680434
[24] train-auc:0.664861 valid-auc:0.680432
[25] train-auc:0.665179 valid-auc:0.680441
[26] train-auc:0.665138 valid-auc:0.680312
[27] train-auc:0.665091 valid-auc:0.680325
[28] train-auc:0.665265 valid-auc:0.681251
[29] train-auc:0.665207 valid-auc:0.681186
[30] train-auc:0.665222 valid-auc:0.681274
[31] train-auc:0.665238 valid-auc:0.681285
[32] train-auc:0.665341 valid-auc:0.680822
[33] train-auc:0.66535 valid-auc:0.680781
[34] train-auc:0.665743 valid-auc:0.68087
[35] train-auc:0.669904 valid-auc:0.685571
[36] train-auc:0.670123 valid-auc:0.685837
[37] train-auc:0.670148 valid-auc:0.685914
[38] train-auc:0.670069 valid-auc:0.686316
[39] train-auc:0.67 valid-auc:0.686074
[40] train-auc:0.66992 valid-auc:0.685922
[41] train-auc:0.670874 valid-auc:0.685699
[42] train-auc:0.671278 valid-auc:0.686159
[43] train-auc:0.671509 valid-auc:0.686153
[44] train-auc:0.67165 valid-auc:0.686316
[45] train-auc:0.671964 valid-auc:0.686209
[46] train-auc:0.672162 valid-auc:0.686079
[47] train-auc:0.672115 valid-auc:0.686073
[48] train-auc:0.672432 valid-auc:0.686061
[49] train-auc:0.672295 valid-auc:0.686301
[50] train-auc:0.672663 valid-auc:0.686256
[51] train-auc:0.672593 valid-auc:0.685702
[52] train-auc:0.673081 valid-auc:0.685867
[53] train-auc:0.673244 valid-auc:0.685972
[54] train-auc:0.673614 valid-auc:0.686246
[55] train-auc:0.674426 valid-auc:0.686984
[56] train-auc:0.675153 valid-auc:0.688028
[57] train-auc:0.675808 valid-auc:0.68883
[58] train-auc:0.676025 valid-auc:0.688701
[59] train-auc:0.676238 valid-auc:0.688675
[60] train-auc:0.677685 valid-auc:0.689032
[61] train-auc:0.678273 valid-auc:0.689004
[62] train-auc:0.679658 valid-auc:0.687549
[63] train-auc:0.679932 valid-auc:0.687805
[64] train-auc:0.67947 valid-auc:0.688888
[65] train-auc:0.680273 valid-auc:0.689082
[66] train-auc:0.680665 valid-auc:0.688851
[67] train-auc:0.680762 valid-auc:0.689226
[68] train-auc:0.681461 valid-auc:0.688844
[69] train-auc:0.682181 valid-auc:0.689288
[70] train-auc:0.682379 valid-auc:0.689293
[71] train-auc:0.682745 valid-auc:0.689312
[72] train-auc:0.68506 valid-auc:0.68685
[73] train-auc:0.68526 valid-auc:0.686401
[74] train-auc:0.690386 valid-auc:0.691616
[75] train-auc:0.690528 valid-auc:0.691865
[76] train-auc:0.692872 valid-auc:0.690526
[77] train-auc:0.693314 valid-auc:0.690618
[78] train-auc:0.693418 valid-auc:0.690218
[79] train-auc:0.694044 valid-auc:0.692373
[80] train-auc:0.697428 valid-auc:0.692624
[81] train-auc:0.697659 valid-auc:0.692701
[82] train-auc:0.699032 valid-auc:0.693713
[83] train-auc:0.699857 valid-auc:0.690384
[84] train-auc:0.70169 valid-auc:0.689506
[85] train-auc:0.701613 valid-auc:0.689514
[86] train-auc:0.702895 valid-auc:0.690734
[87] train-auc:0.703313 valid-auc:0.691062
[88] train-auc:0.706026 valid-auc:0.691528
[89] train-auc:0.707897 valid-auc:0.692122
[90] train-auc:0.709292 valid-auc:0.692582
[91] train-auc:0.709859 valid-auc:0.693256
[92] train-auc:0.710284 valid-auc:0.693515
[93] train-auc:0.710957 valid-auc:0.69355
[94] train-auc:0.712328 valid-auc:0.69227
[95] train-auc:0.712417 valid-auc:0.691757
[96] train-auc:0.71204 valid-auc:0.691651
[97] train-auc:0.711711 valid-auc:0.691557
[98] train-auc:0.711835 valid-auc:0.691566
[99] train-auc:0.713542 valid-auc:0.691948
[100] train-auc:0.71367 valid-auc:0.691898
[101] train-auc:0.713669 valid-auc:0.691848
[102] train-auc:0.713582 valid-auc:0.69233
[103] train-auc:0.714486 valid-auc:0.691905
[104] train-auc:0.7141 valid-auc:0.691822
[105] train-auc:0.715015 valid-auc:0.690388
[106] train-auc:0.715104 valid-auc:0.690197
[107] train-auc:0.717202 valid-auc:0.690759
[108] train-auc:0.717328 valid-auc:0.690733
[109] train-auc:0.717235 valid-auc:0.690704
[110] train-auc:0.717294 valid-auc:0.690656
[111] train-auc:0.717844 valid-auc:0.689888
[112] train-auc:0.717871 valid-auc:0.689812
[113] train-auc:0.717848 valid-auc:0.689784
[114] train-auc:0.719579 valid-auc:0.691484
[115] train-auc:0.720123 valid-auc:0.691407
[116] train-auc:0.720771 valid-auc:0.689881
[117] train-auc:0.720929 valid-auc:0.690458
[118] train-auc:0.721102 valid-auc:0.690552
[119] train-auc:0.721787 valid-auc:0.690719
[120] train-auc:0.723621 valid-auc:0.690898
[121] train-auc:0.723621 valid-auc:0.690898
[122] train-auc:0.723611 valid-auc:0.69073
[123] train-auc:0.723715 valid-auc:0.690682
[124] train-auc:0.723697 valid-auc:0.690804
[125] train-auc:0.724071 valid-auc:0.69185
[126] train-auc:0.724599 valid-auc:0.692426
[127] train-auc:0.725189 valid-auc:0.692239
[128] train-auc:0.72552 valid-auc:0.691791
[129] train-auc:0.725466 valid-auc:0.691597
[130] train-auc:0.725448 valid-auc:0.691603
[131] train-auc:0.725965 valid-auc:0.691891
[132] train-auc:0.726354 valid-auc:0.691797
Stopping. Best iteration:
[82] train-auc:0.699032 valid-auc:0.693713
[mlcrate] Finished training fold 2 - took 4s - running score 0.6888706666666667
[mlcrate] Running fold 3, 15737 train samples, 2622 validation samples
[0] train-auc:0.619301 valid-auc:0.588993
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.634717 valid-auc:0.603446
[2] train-auc:0.634992 valid-auc:0.603179
[3] train-auc:0.65075 valid-auc:0.611919
[4] train-auc:0.650936 valid-auc:0.611919
[5] train-auc:0.650896 valid-auc:0.611963
[6] train-auc:0.650896 valid-auc:0.611963
[7] train-auc:0.6543 valid-auc:0.614752
[8] train-auc:0.656322 valid-auc:0.616055
[9] train-auc:0.656328 valid-auc:0.61608
[10] train-auc:0.65643 valid-auc:0.616167
[11] train-auc:0.65692 valid-auc:0.616566
[12] train-auc:0.656876 valid-auc:0.616596
[13] train-auc:0.656913 valid-auc:0.616605
[14] train-auc:0.65688 valid-auc:0.616616
[15] train-auc:0.656728 valid-auc:0.616582
[16] train-auc:0.658461 valid-auc:0.617489
[17] train-auc:0.658693 valid-auc:0.617954
[18] train-auc:0.658725 valid-auc:0.617902
[19] train-auc:0.658708 valid-auc:0.617975
[20] train-auc:0.658747 valid-auc:0.617817
[21] train-auc:0.659942 valid-auc:0.61634
[22] train-auc:0.66023 valid-auc:0.61642
[23] train-auc:0.660254 valid-auc:0.616493
[24] train-auc:0.660242 valid-auc:0.616567
[25] train-auc:0.660226 valid-auc:0.616456
[26] train-auc:0.660161 valid-auc:0.616819
[27] train-auc:0.660415 valid-auc:0.617756
[28] train-auc:0.660873 valid-auc:0.617696
[29] train-auc:0.660831 valid-auc:0.617573
[30] train-auc:0.660864 valid-auc:0.617251
[31] train-auc:0.660855 valid-auc:0.617441
[32] train-auc:0.661896 valid-auc:0.6187
[33] train-auc:0.661951 valid-auc:0.618503
[34] train-auc:0.662117 valid-auc:0.618812
[35] train-auc:0.662148 valid-auc:0.618856
[36] train-auc:0.662083 valid-auc:0.618644
[37] train-auc:0.67351 valid-auc:0.63427
[38] train-auc:0.673681 valid-auc:0.634522
[39] train-auc:0.673654 valid-auc:0.634587
[40] train-auc:0.677131 valid-auc:0.638519
[41] train-auc:0.677258 valid-auc:0.639248
[42] train-auc:0.678046 valid-auc:0.639356
[43] train-auc:0.678349 valid-auc:0.639418
[44] train-auc:0.678306 valid-auc:0.639238
[45] train-auc:0.678965 valid-auc:0.639176
[46] train-auc:0.679053 valid-auc:0.639115
[47] train-auc:0.678935 valid-auc:0.639101
[48] train-auc:0.679326 valid-auc:0.639081
[49] train-auc:0.679151 valid-auc:0.639058
[50] train-auc:0.681722 valid-auc:0.640361
[51] train-auc:0.682259 valid-auc:0.640705
[52] train-auc:0.682637 valid-auc:0.641312
[53] train-auc:0.683363 valid-auc:0.641273
[54] train-auc:0.68382 valid-auc:0.641427
[55] train-auc:0.684304 valid-auc:0.641817
[56] train-auc:0.684336 valid-auc:0.641457
[57] train-auc:0.684574 valid-auc:0.641418
[58] train-auc:0.684677 valid-auc:0.641433
[59] train-auc:0.684941 valid-auc:0.642061
[60] train-auc:0.684845 valid-auc:0.641537
[61] train-auc:0.684981 valid-auc:0.641392
[62] train-auc:0.685124 valid-auc:0.641551
[63] train-auc:0.685782 valid-auc:0.642038
[64] train-auc:0.685898 valid-auc:0.641792
[65] train-auc:0.686134 valid-auc:0.641721
[66] train-auc:0.686821 valid-auc:0.643029
[67] train-auc:0.687037 valid-auc:0.643118
[68] train-auc:0.688925 valid-auc:0.640807
[69] train-auc:0.689858 valid-auc:0.641249
[70] train-auc:0.698392 valid-auc:0.644806
[71] train-auc:0.698977 valid-auc:0.646639
[72] train-auc:0.700992 valid-auc:0.645614
[73] train-auc:0.701343 valid-auc:0.645571
[74] train-auc:0.702147 valid-auc:0.645825
[75] train-auc:0.70517 valid-auc:0.648234
[76] train-auc:0.705606 valid-auc:0.647784
[77] train-auc:0.708867 valid-auc:0.647714
[78] train-auc:0.709169 valid-auc:0.647916
[79] train-auc:0.709542 valid-auc:0.647423
[80] train-auc:0.709586 valid-auc:0.647206
[81] train-auc:0.711256 valid-auc:0.646933
[82] train-auc:0.71301 valid-auc:0.646617
[83] train-auc:0.713446 valid-auc:0.64786
[84] train-auc:0.71505 valid-auc:0.647019
[85] train-auc:0.717239 valid-auc:0.644783
[86] train-auc:0.718234 valid-auc:0.644921
[87] train-auc:0.718335 valid-auc:0.644909
[88] train-auc:0.71862 valid-auc:0.644901
[89] train-auc:0.719787 valid-auc:0.644545
[90] train-auc:0.720751 valid-auc:0.644676
[91] train-auc:0.720555 valid-auc:0.644629
[92] train-auc:0.721104 valid-auc:0.64463
[93] train-auc:0.721434 valid-auc:0.645276
[94] train-auc:0.72164 valid-auc:0.645342
[95] train-auc:0.721851 valid-auc:0.645293
[96] train-auc:0.721736 valid-auc:0.645421
[97] train-auc:0.722617 valid-auc:0.648175
[98] train-auc:0.723207 valid-auc:0.648349
[99] train-auc:0.72333 valid-auc:0.648486
[100] train-auc:0.724151 valid-auc:0.647779
[101] train-auc:0.725154 valid-auc:0.648184
[102] train-auc:0.725393 valid-auc:0.647785
[103] train-auc:0.726443 valid-auc:0.646884
[104] train-auc:0.726886 valid-auc:0.646591
[105] train-auc:0.727276 valid-auc:0.646731
[106] train-auc:0.72937 valid-auc:0.646927
[107] train-auc:0.730728 valid-auc:0.64789
[108] train-auc:0.731336 valid-auc:0.646896
[109] train-auc:0.731691 valid-auc:0.647523
[110] train-auc:0.731806 valid-auc:0.647572
[111] train-auc:0.732686 valid-auc:0.647625
[112] train-auc:0.733137 valid-auc:0.64756
[113] train-auc:0.733358 valid-auc:0.647951
[114] train-auc:0.73335 valid-auc:0.647909
[115] train-auc:0.733632 valid-auc:0.647612
[116] train-auc:0.733874 valid-auc:0.647215
[117] train-auc:0.733566 valid-auc:0.64716
[118] train-auc:0.733554 valid-auc:0.646969
[119] train-auc:0.733455 valid-auc:0.646935
[120] train-auc:0.734109 valid-auc:0.646551
[121] train-auc:0.733996 valid-auc:0.646488
[122] train-auc:0.734573 valid-auc:0.646498
[123] train-auc:0.735018 valid-auc:0.64643
[124] train-auc:0.736807 valid-auc:0.645798
[125] train-auc:0.738035 valid-auc:0.646035
[126] train-auc:0.737997 valid-auc:0.646445
[127] train-auc:0.737997 valid-auc:0.646445
[128] train-auc:0.738204 valid-auc:0.646689
[129] train-auc:0.738694 valid-auc:0.646434
[130] train-auc:0.739085 valid-auc:0.646662
[131] train-auc:0.739216 valid-auc:0.646564
[132] train-auc:0.739827 valid-auc:0.646163
[133] train-auc:0.740021 valid-auc:0.646069
[134] train-auc:0.740859 valid-auc:0.646009
[135] train-auc:0.740859 valid-auc:0.646009
[136] train-auc:0.741043 valid-auc:0.646156
[137] train-auc:0.741453 valid-auc:0.646114
[138] train-auc:0.74163 valid-auc:0.646048
[139] train-auc:0.741588 valid-auc:0.645949
[140] train-auc:0.742042 valid-auc:0.646274
[141] train-auc:0.742638 valid-auc:0.645959
[142] train-auc:0.742638 valid-auc:0.645959
[143] train-auc:0.742718 valid-auc:0.645943
[144] train-auc:0.742822 valid-auc:0.646008
[145] train-auc:0.74408 valid-auc:0.645883
[146] train-auc:0.74408 valid-auc:0.645883
[147] train-auc:0.74408 valid-auc:0.645883
[148] train-auc:0.744629 valid-auc:0.645719
[149] train-auc:0.744723 valid-auc:0.645576
Stopping. Best iteration:
[99] train-auc:0.72333 valid-auc:0.648486
[mlcrate] Finished training fold 3 - took 5s - running score 0.6787745000000001
[mlcrate] Running fold 4, 15737 train samples, 2622 validation samples
[0] train-auc:0.618735 valid-auc:0.590751
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.641281 valid-auc:0.624215
[2] train-auc:0.641441 valid-auc:0.624695
[3] train-auc:0.643289 valid-auc:0.625606
[4] train-auc:0.651247 valid-auc:0.635947
[5] train-auc:0.651247 valid-auc:0.635951
[6] train-auc:0.651554 valid-auc:0.636102
[7] train-auc:0.651524 valid-auc:0.636024
[8] train-auc:0.651524 valid-auc:0.636024
[9] train-auc:0.651585 valid-auc:0.635965
[10] train-auc:0.65188 valid-auc:0.636586
[11] train-auc:0.6519 valid-auc:0.636643
[12] train-auc:0.651819 valid-auc:0.636697
[13] train-auc:0.651914 valid-auc:0.636686
[14] train-auc:0.654168 valid-auc:0.639708
[15] train-auc:0.654196 valid-auc:0.63988
[16] train-auc:0.654213 valid-auc:0.639544
[17] train-auc:0.65423 valid-auc:0.639558
[18] train-auc:0.654219 valid-auc:0.639509
[19] train-auc:0.654277 valid-auc:0.639667
[20] train-auc:0.654323 valid-auc:0.640174
[21] train-auc:0.654285 valid-auc:0.640167
[22] train-auc:0.654271 valid-auc:0.640133
[23] train-auc:0.654642 valid-auc:0.640815
[24] train-auc:0.654657 valid-auc:0.640756
[25] train-auc:0.657001 valid-auc:0.640481
[26] train-auc:0.656935 valid-auc:0.640695
[27] train-auc:0.656946 valid-auc:0.640745
[28] train-auc:0.657087 valid-auc:0.641824
[29] train-auc:0.6575 valid-auc:0.64263
[30] train-auc:0.659203 valid-auc:0.641485
[31] train-auc:0.659465 valid-auc:0.641262
[32] train-auc:0.659594 valid-auc:0.641163
[33] train-auc:0.659993 valid-auc:0.640775
[34] train-auc:0.660461 valid-auc:0.640264
[35] train-auc:0.665222 valid-auc:0.641288
[36] train-auc:0.674865 valid-auc:0.652817
[37] train-auc:0.674975 valid-auc:0.652855
[38] train-auc:0.674921 valid-auc:0.653352
[39] train-auc:0.675234 valid-auc:0.654388
[40] train-auc:0.675533 valid-auc:0.654494
[41] train-auc:0.675574 valid-auc:0.654419
[42] train-auc:0.675429 valid-auc:0.654568
[43] train-auc:0.675272 valid-auc:0.654549
[44] train-auc:0.675551 valid-auc:0.654567
[45] train-auc:0.675624 valid-auc:0.65816
[46] train-auc:0.676259 valid-auc:0.657933
[47] train-auc:0.677153 valid-auc:0.656657
[48] train-auc:0.679759 valid-auc:0.656257
[49] train-auc:0.680439 valid-auc:0.656238
[50] train-auc:0.68053 valid-auc:0.656448
[51] train-auc:0.680689 valid-auc:0.656675
[52] train-auc:0.680765 valid-auc:0.656527
[53] train-auc:0.68187 valid-auc:0.656647
[54] train-auc:0.682826 valid-auc:0.655963
[55] train-auc:0.683126 valid-auc:0.655975
[56] train-auc:0.683165 valid-auc:0.655725
[57] train-auc:0.68333 valid-auc:0.655919
[58] train-auc:0.68382 valid-auc:0.655667
[59] train-auc:0.684619 valid-auc:0.654834
[60] train-auc:0.684986 valid-auc:0.654497
[61] train-auc:0.685504 valid-auc:0.654378
[62] train-auc:0.686192 valid-auc:0.654127
[63] train-auc:0.686874 valid-auc:0.654453
[64] train-auc:0.687639 valid-auc:0.654349
[65] train-auc:0.688324 valid-auc:0.656462
[66] train-auc:0.688426 valid-auc:0.656615
[67] train-auc:0.688715 valid-auc:0.656815
[68] train-auc:0.689091 valid-auc:0.655633
[69] train-auc:0.689589 valid-auc:0.655558
[70] train-auc:0.690257 valid-auc:0.655309
[71] train-auc:0.697946 valid-auc:0.653646
[72] train-auc:0.698409 valid-auc:0.653873
[73] train-auc:0.699949 valid-auc:0.657017
[74] train-auc:0.699807 valid-auc:0.657224
[75] train-auc:0.7035 valid-auc:0.653871
[76] train-auc:0.703786 valid-auc:0.653716
[77] train-auc:0.703864 valid-auc:0.653863
[78] train-auc:0.704308 valid-auc:0.653944
[79] train-auc:0.704828 valid-auc:0.653645
[80] train-auc:0.70497 valid-auc:0.653817
[81] train-auc:0.70527 valid-auc:0.653615
[82] train-auc:0.705153 valid-auc:0.653754
[83] train-auc:0.708833 valid-auc:0.653012
[84] train-auc:0.708962 valid-auc:0.653317
[85] train-auc:0.709541 valid-auc:0.653238
[86] train-auc:0.709976 valid-auc:0.651927
[87] train-auc:0.710208 valid-auc:0.652554
[88] train-auc:0.711198 valid-auc:0.653624
[89] train-auc:0.711738 valid-auc:0.6535
[90] train-auc:0.712659 valid-auc:0.652723
[91] train-auc:0.714727 valid-auc:0.65321
[92] train-auc:0.715173 valid-auc:0.653297
[93] train-auc:0.717051 valid-auc:0.653128
[94] train-auc:0.718616 valid-auc:0.653349
[95] train-auc:0.71888 valid-auc:0.653695
Stopping. Best iteration:
[45] train-auc:0.675624 valid-auc:0.65816
[mlcrate] Finished training fold 4 - took 3s - running score 0.6746516
[mlcrate] Running fold 5, 15737 train samples, 2622 validation samples
[0] train-auc:0.617167 valid-auc:0.601804
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.617272 valid-auc:0.601971
[2] train-auc:0.642764 valid-auc:0.627919
[3] train-auc:0.647333 valid-auc:0.631363
[4] train-auc:0.650566 valid-auc:0.633426
[5] train-auc:0.650564 valid-auc:0.633426
[6] train-auc:0.654694 valid-auc:0.633057
[7] train-auc:0.654677 valid-auc:0.63301
[8] train-auc:0.654713 valid-auc:0.633975
[9] train-auc:0.654546 valid-auc:0.634076
[10] train-auc:0.654593 valid-auc:0.634105
[11] train-auc:0.654567 valid-auc:0.634105
[12] train-auc:0.654485 valid-auc:0.634073
[13] train-auc:0.6553 valid-auc:0.634956
[14] train-auc:0.655477 valid-auc:0.634926
[15] train-auc:0.655418 valid-auc:0.634985
[16] train-auc:0.655405 valid-auc:0.634964
[17] train-auc:0.655368 valid-auc:0.634775
[18] train-auc:0.655469 valid-auc:0.634364
[19] train-auc:0.656418 valid-auc:0.63258
[20] train-auc:0.656533 valid-auc:0.63257
[21] train-auc:0.656564 valid-auc:0.632499
[22] train-auc:0.65644 valid-auc:0.632457
[23] train-auc:0.656584 valid-auc:0.632617
[24] train-auc:0.656675 valid-auc:0.632902
[25] train-auc:0.656868 valid-auc:0.63259
[26] train-auc:0.656809 valid-auc:0.632451
[27] train-auc:0.658169 valid-auc:0.634921
[28] train-auc:0.658351 valid-auc:0.635137
[29] train-auc:0.658843 valid-auc:0.635099
[30] train-auc:0.658833 valid-auc:0.635178
[31] train-auc:0.658823 valid-auc:0.635392
[32] train-auc:0.65939 valid-auc:0.635672
[33] train-auc:0.659331 valid-auc:0.635617
[34] train-auc:0.659285 valid-auc:0.635594
[35] train-auc:0.659438 valid-auc:0.635636
[36] train-auc:0.659447 valid-auc:0.635747
[37] train-auc:0.659633 valid-auc:0.63577
[38] train-auc:0.660346 valid-auc:0.63605
[39] train-auc:0.660314 valid-auc:0.636207
[40] train-auc:0.660264 valid-auc:0.636104
[41] train-auc:0.660319 valid-auc:0.63613
[42] train-auc:0.662757 valid-auc:0.64214
[43] train-auc:0.66313 valid-auc:0.641877
[44] train-auc:0.663512 valid-auc:0.642509
[45] train-auc:0.663496 valid-auc:0.642478
[46] train-auc:0.671491 valid-auc:0.653026
[47] train-auc:0.671606 valid-auc:0.652503
[48] train-auc:0.67191 valid-auc:0.652415
[49] train-auc:0.674747 valid-auc:0.657342
[50] train-auc:0.677368 valid-auc:0.660285
[51] train-auc:0.678543 valid-auc:0.663993
[52] train-auc:0.678578 valid-auc:0.663808
[53] train-auc:0.679907 valid-auc:0.664191
[54] train-auc:0.681655 valid-auc:0.663462
[55] train-auc:0.681946 valid-auc:0.663586
[56] train-auc:0.683393 valid-auc:0.662815
[57] train-auc:0.68359 valid-auc:0.662785
[58] train-auc:0.683917 valid-auc:0.662772
[59] train-auc:0.684414 valid-auc:0.662819
[60] train-auc:0.685414 valid-auc:0.662735
[61] train-auc:0.685482 valid-auc:0.663068
[62] train-auc:0.68593 valid-auc:0.662735
[63] train-auc:0.685937 valid-auc:0.66269
[64] train-auc:0.686155 valid-auc:0.662836
[65] train-auc:0.686682 valid-auc:0.662639
[66] train-auc:0.686765 valid-auc:0.662589
[67] train-auc:0.687211 valid-auc:0.662367
[68] train-auc:0.687615 valid-auc:0.662029
[69] train-auc:0.687692 valid-auc:0.662047
[70] train-auc:0.688236 valid-auc:0.662041
[71] train-auc:0.689988 valid-auc:0.664578
[72] train-auc:0.693449 valid-auc:0.668186
[73] train-auc:0.69416 valid-auc:0.668473
[74] train-auc:0.695455 valid-auc:0.668823
[75] train-auc:0.695795 valid-auc:0.669016
[76] train-auc:0.698951 valid-auc:0.669695
[77] train-auc:0.699167 valid-auc:0.668977
[78] train-auc:0.699195 valid-auc:0.668365
[79] train-auc:0.699649 valid-auc:0.667649
[80] train-auc:0.699593 valid-auc:0.667577
[81] train-auc:0.699555 valid-auc:0.667483
[82] train-auc:0.701904 valid-auc:0.667798
[83] train-auc:0.702102 valid-auc:0.668195
[84] train-auc:0.70237 valid-auc:0.668278
[85] train-auc:0.702675 valid-auc:0.668997
[86] train-auc:0.703044 valid-auc:0.669034
[87] train-auc:0.705302 valid-auc:0.667941
[88] train-auc:0.70553 valid-auc:0.667786
[89] train-auc:0.706263 valid-auc:0.668099
[90] train-auc:0.705965 valid-auc:0.667472
[91] train-auc:0.706745 valid-auc:0.667198
[92] train-auc:0.70861 valid-auc:0.669174
[93] train-auc:0.709307 valid-auc:0.670546
[94] train-auc:0.710074 valid-auc:0.67041
[95] train-auc:0.710681 valid-auc:0.670364
[96] train-auc:0.713333 valid-auc:0.669838
[97] train-auc:0.714313 valid-auc:0.669551
[98] train-auc:0.714939 valid-auc:0.669916
[99] train-auc:0.714909 valid-auc:0.669537
[100] train-auc:0.715119 valid-auc:0.669288
[101] train-auc:0.716083 valid-auc:0.668977
[102] train-auc:0.716041 valid-auc:0.669026
[103] train-auc:0.717452 valid-auc:0.669433
[104] train-auc:0.717884 valid-auc:0.669398
[105] train-auc:0.718485 valid-auc:0.668715
[106] train-auc:0.718572 valid-auc:0.668831
[107] train-auc:0.718657 valid-auc:0.668495
[108] train-auc:0.719495 valid-auc:0.668761
[109] train-auc:0.71952 valid-auc:0.668929
[110] train-auc:0.720915 valid-auc:0.668476
[111] train-auc:0.720779 valid-auc:0.668544
[112] train-auc:0.721376 valid-auc:0.668237
[113] train-auc:0.721869 valid-auc:0.667782
[114] train-auc:0.722127 valid-auc:0.667975
[115] train-auc:0.722317 valid-auc:0.668272
[116] train-auc:0.722425 valid-auc:0.668304
[117] train-auc:0.723093 valid-auc:0.667582
[118] train-auc:0.723566 valid-auc:0.667643
[119] train-auc:0.724402 valid-auc:0.667685
[120] train-auc:0.725187 valid-auc:0.668114
[121] train-auc:0.72577 valid-auc:0.6686
[122] train-auc:0.726044 valid-auc:0.668581
[123] train-auc:0.726788 valid-auc:0.668682
[124] train-auc:0.727073 valid-auc:0.669106
[125] train-auc:0.727065 valid-auc:0.669044
[126] train-auc:0.728095 valid-auc:0.668893
[127] train-auc:0.72895 valid-auc:0.668705
[128] train-auc:0.72944 valid-auc:0.668396
[129] train-auc:0.730554 valid-auc:0.667914
[130] train-auc:0.730837 valid-auc:0.667783
[131] train-auc:0.731443 valid-auc:0.667546
[132] train-auc:0.732596 valid-auc:0.666826
[133] train-auc:0.733349 valid-auc:0.666939
[134] train-auc:0.734244 valid-auc:0.667276
[135] train-auc:0.734729 valid-auc:0.667307
[136] train-auc:0.735365 valid-auc:0.666801
[137] train-auc:0.737257 valid-auc:0.666376
[138] train-auc:0.737693 valid-auc:0.666735
[139] train-auc:0.737978 valid-auc:0.666897
[140] train-auc:0.738461 valid-auc:0.666437
[141] train-auc:0.738739 valid-auc:0.6663
[142] train-auc:0.738934 valid-auc:0.666587
[143] train-auc:0.740088 valid-auc:0.665821
Stopping. Best iteration:
[93] train-auc:0.709307 valid-auc:0.670546
[mlcrate] Finished training fold 5 - took 5s - running score 0.6739673333333335
[mlcrate] Running fold 6, 15737 train samples, 2622 validation samples
[0] train-auc:0.631235 valid-auc:0.62788
Multiple eval metrics have been passed: 'valid-auc' will be used for early stopping.
Will train until valid-auc hasn't improved in 50 rounds.
[1] train-auc:0.640451 valid-auc:0.636418
[2] train-auc:0.641973 valid-auc:0.637578
[3] train-auc:0.647673 valid-auc:0.642467
[4] train-auc:0.647667 valid-auc:0.642347
[5] train-auc:0.650001 valid-auc:0.645022
[6] train-auc:0.650054 valid-auc:0.645394
[7] train-auc:0.649953 valid-auc:0.645306
[8] train-auc:0.654315 valid-auc:0.645522
[9] train-auc:0.654326 valid-auc:0.645552
[10] train-auc:0.654363 valid-auc:0.645502
[11] train-auc:0.655826 valid-auc:0.645509
[12] train-auc:0.655774 valid-auc:0.645552
[13] train-auc:0.655893 valid-auc:0.645555
[14] train-auc:0.655885 valid-auc:0.645547
[15] train-auc:0.655837 valid-auc:0.645818
[16] train-auc:0.657403 valid-auc:0.647186
[17] train-auc:0.657357 valid-auc:0.64715
[18] train-auc:0.657452 valid-auc:0.646964
[19] train-auc:0.657504 valid-auc:0.647112
[20] train-auc:0.657506 valid-auc:0.647074
[21] train-auc:0.657499 valid-auc:0.647149
[22] train-auc:0.657433 valid-auc:0.647305
[23] train-auc:0.657645 valid-auc:0.647399
[24] train-auc:0.657651 valid-auc:0.647089
[25] train-auc:0.658785 valid-auc:0.646708
[26] train-auc:0.659365 valid-auc:0.646711
[27] train-auc:0.660681 valid-auc:0.646875
[28] train-auc:0.660557 valid-auc:0.646612
[29] train-auc:0.660674 valid-auc:0.646777
[30] train-auc:0.660709 valid-auc:0.646953
[31] train-auc:0.660645 valid-auc:0.647035
[32] train-auc:0.660858 valid-auc:0.647072
[33] train-auc:0.660797 valid-auc:0.647284
[34] train-auc:0.660892 valid-auc:0.647041
[35] train-auc:0.672506 valid-auc:0.65495
[36] train-auc:0.67285 valid-auc:0.654733
[37] train-auc:0.67334 valid-auc:0.657998
[38] train-auc:0.673655 valid-auc:0.658191
[39] train-auc:0.673623 valid-auc:0.658112
[40] train-auc:0.673765 valid-auc:0.658447
[41] train-auc:0.673822 valid-auc:0.658487
[42] train-auc:0.6739 valid-auc:0.658788
[43] train-auc:0.674063 valid-auc:0.65901
[44] train-auc:0.674717 valid-auc:0.658803
[45] train-auc:0.675131 valid-auc:0.658839
[46] train-auc:0.675205 valid-auc:0.658586
[47] train-auc:0.675693 valid-auc:0.658654
[48] train-auc:0.675599 valid-auc:0.658377
[49] train-auc:0.679738 valid-auc:0.657402
[50] train-auc:0.679816 valid-auc:0.657473
[51] train-auc:0.679848 valid-auc:0.657843
[52] train-auc:0.680001 valid-auc:0.657521
[53] train-auc:0.680503 valid-auc:0.657605
[54] train-auc:0.680861 valid-auc:0.657919
[55] train-auc:0.681124 valid-auc:0.660746
[56] train-auc:0.681187 valid-auc:0.660758
[57] train-auc:0.682062 valid-auc:0.660727
[58] train-auc:0.682195 valid-auc:0.660884
[59] train-auc:0.682707 valid-auc:0.660843
[60] train-auc:0.683303 valid-auc:0.661658
[61] train-auc:0.683921 valid-auc:0.66156
[62] train-auc:0.683995 valid-auc:0.661294
[63] train-auc:0.684007 valid-auc:0.662409
[64] train-auc:0.685036 valid-auc:0.661509
[65] train-auc:0.686802 valid-auc:0.658935
[66] train-auc:0.687242 valid-auc:0.659007
[67] train-auc:0.687117 valid-auc:0.661294
[68] train-auc:0.687589 valid-auc:0.661643
[69] train-auc:0.687689 valid-auc:0.661607
[70] train-auc:0.688312 valid-auc:0.661781
[71] train-auc:0.689633 valid-auc:0.661758
[72] train-auc:0.68993 valid-auc:0.661312
[73] train-auc:0.690234 valid-auc:0.661492
[74] train-auc:0.690852 valid-auc:0.661518
[75] train-auc:0.693427 valid-auc:0.666813
[76] train-auc:0.694166 valid-auc:0.665624
[77] train-auc:0.69475 valid-auc:0.665815
[78] train-auc:0.697219 valid-auc:0.667697
[79] train-auc:0.701199 valid-auc:0.667701
[80] train-auc:0.70276 valid-auc:0.666735
[81] train-auc:0.705767 valid-auc:0.666784
[82] train-auc:0.706013 valid-auc:0.666571
[83] train-auc:0.705909 valid-auc:0.666648
[84] train-auc:0.707101 valid-auc:0.667439
[85] train-auc:0.70854 valid-auc:0.666962
[86] train-auc:0.708622 valid-auc:0.666814
[87] train-auc:0.709147 valid-auc:0.667066
[88] train-auc:0.710326 valid-auc:0.667207
[89] train-auc:0.71092 valid-auc:0.66769
[90] train-auc:0.71184 valid-auc:0.668609
[91] train-auc:0.712747 valid-auc:0.669511
[92] train-auc:0.714795 valid-auc:0.669148
[93] train-auc:0.716183 valid-auc:0.667662
[94] train-auc:0.716141 valid-auc:0.668247
[95] train-auc:0.716995 valid-auc:0.668816
[96] train-auc:0.71751 valid-auc:0.668476
[97] train-auc:0.719129 valid-auc:0.667233
[98] train-auc:0.721116 valid-auc:0.666451
[99] train-auc:0.720861 valid-auc:0.666566
[100] train-auc:0.721689 valid-auc:0.66603
[101] train-auc:0.72148 valid-auc:0.665846
[102] train-auc:0.721537 valid-auc:0.666231
[103] train-auc:0.72163 valid-auc:0.666214
[104] train-auc:0.722332 valid-auc:0.665586
[105] train-auc:0.722813 valid-auc:0.66708
[106] train-auc:0.722742 valid-auc:0.667093
[107] train-auc:0.72305 valid-auc:0.667213
[108] train-auc:0.724063 valid-auc:0.667913
[109] train-auc:0.724749 valid-auc:0.667441
[110] train-auc:0.725173 valid-auc:0.667706
[111] train-auc:0.725173 valid-auc:0.667706
[112] train-auc:0.725407 valid-auc:0.668459
[113] train-auc:0.725999 valid-auc:0.667912
[114] train-auc:0.726286 valid-auc:0.66787
[115] train-auc:0.727397 valid-auc:0.668735
[116] train-auc:0.728414 valid-auc:0.669009
[117] train-auc:0.728841 valid-auc:0.668252
[118] train-auc:0.728795 valid-auc:0.668857
[119] train-auc:0.730745 valid-auc:0.669075
[120] train-auc:0.731204 valid-auc:0.669086
[121] train-auc:0.731124 valid-auc:0.669138
[122] train-auc:0.731387 valid-auc:0.669226
[123] train-auc:0.732108 valid-auc:0.669086
[124] train-auc:0.731839 valid-auc:0.669035
[125] train-auc:0.732575 valid-auc:0.668275
[126] train-auc:0.732724 valid-auc:0.66829
[127] train-auc:0.732796 valid-auc:0.668135
[128] train-auc:0.732759 valid-auc:0.667939
[129] train-auc:0.732993 valid-auc:0.668243
[130] train-auc:0.733357 valid-auc:0.668303
[131] train-auc:0.733357 valid-auc:0.668303
[132] train-auc:0.735009 valid-auc:0.667884
[133] train-auc:0.736868 valid-auc:0.668662
[134] train-auc:0.737641 valid-auc:0.669238
[135] train-auc:0.73856 valid-auc:0.669102
[136] train-auc:0.739614 valid-auc:0.668805
[137] train-auc:0.739753 valid-auc:0.668923
[138] train-auc:0.739975 valid-auc:0.668332
[139] train-auc:0.740553 valid-auc:0.668667
[140] train-auc:0.741669 valid-auc:0.668645
[141] train-auc:0.742404 valid-auc:0.668931
Stopping. Best iteration:
[91] train-auc:0.712747 valid-auc:0.669511
[mlcrate] Finished training fold 6 - took 4s - running score 0.6733307142857143
[mlcrate] Finished training 7 XGBoost models, took 31s
In [ ]:
Content source: AdityaSoni19031997/Machine-Learning
Similar notebooks: