In [1]:
%load_ext autoreload
%autoreload 2
%matplotlib inline
In [2]:
from sklearn.ensemble import RandomForestRegressor, RandomForestClassifier
from fastai.imports import *
from fastai.structured import *
from pandas_summary import DataFrameSummary
from IPython.display import display
from sklearn import metrics
from sklearn import metrics
import warnings
warnings.filterwarnings('ignore')
import seaborn as sns
sns.set()
from sklearn.preprocessing import StandardScaler
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression
from xgboost import XGBRegressor
from sklearn.metrics import roc_auc_score
In [3]:
import os
PATH = os.getcwd();
PATH = PATH+'\\AV_Mckin\\ods\\';
PATH
Out[3]:
'D:\\Github\\fastai\\courses\\ml1\\AV_Mckin\\ods\\'
In [57]:
df_train_org = pd.read_csv(f'{PATH}\\flight_delays_train.csv', low_memory=False)
df_test_org = pd.read_csv(f'{PATH}\\flight_delays_test.csv', low_memory=False)
df_raw = pd.read_csv(f'{PATH}\\impact_encoded_train.csv', low_memory=False)
df_test = pd.read_csv(f'{PATH}\\impact_encoded_test.csv', low_memory=False)
In [58]:
df_raw.head(2)
Out[58]:
Month
DayofMonth
DayOfWeek
DepTime
UniqueCarrier
Origin
Dest
Distance
target
impact_encoded_Month
impact_encoded_DayofMonth
impact_encoded_DayOfWeek
impact_encoded_UniqueCarrier
impact_encoded_Origin
impact_encoded_Dest
0
c-8
c-21
c-7
1934
AA
ATL
DFW
732
0
0.202561
0.202928
0.191829
0.186803
0.258108
0.148708
1
c-4
c-20
c-3
1548
US
PIT
MCO
834
0
0.155567
0.213503
0.176398
0.167930
0.178860
0.177618
In [8]:
from sklearn.model_selection import train_test_split
In [65]:
def preprocess(X):
X["Flight"] = X["Origin"] + "-" + X["Dest"]
X["Hour"] = X["DepTime"] // 100
X['Mins'] = X['DepTime'] % 100
X["Month"] = X["Month"].apply(lambda x: int(x.split('-')[1]))
X["DayOfMonth"] = X["DayofMonth"].apply(lambda x: int(x.split('-')[1]))
X = X.drop(["DayofMonth"], axis=1)
X['DayOfWeek'] = X['DayOfWeek'].apply(lambda x: int(x.split('-')[1]))
X['weekend'] = np.where(X['DayOfWeek']>=6,1,0)
return X
In [66]:
df_raw = preprocess(df_raw.copy())
df_test = preprocess(df_test.copy())
In [67]:
y = df_raw.target.values
df_raw.drop('target',axis=1,inplace=True)
categorical_features_indices = np.where(df_raw.dtypes == object)[0]
categorical_features_indices
Out[67]:
array([ 3, 4, 5, 13], dtype=int64)
In [68]:
from sklearn.model_selection import train_test_split
X_train, X_validation, y_train, y_validation = train_test_split(df_raw, y, train_size=0.8, random_state=1234);
In [69]:
#importing library and building model
from catboost import CatBoostClassifier
model=CatBoostClassifier(iterations=1000, depth=10, learning_rate=0.01, loss_function='CrossEntropy',\
)
model.fit(X_train, y_train,cat_features=categorical_features_indices,eval_set=(X_validation, y_validation))
0: learn: 0.6877879 test: 0.6877784 best: 0.6877784 (0) total: 207ms remaining: 3m 27s
1: learn: 0.6825222 test: 0.6824822 best: 0.6824822 (1) total: 533ms remaining: 4m 25s
2: learn: 0.6771314 test: 0.6770637 best: 0.6770637 (2) total: 820ms remaining: 4m 32s
3: learn: 0.6722187 test: 0.6720943 best: 0.6720943 (3) total: 976ms remaining: 4m 2s
4: learn: 0.6671047 test: 0.6669208 best: 0.6669208 (4) total: 1.4s remaining: 4m 37s
5: learn: 0.6621384 test: 0.6619802 best: 0.6619802 (5) total: 1.67s remaining: 4m 37s
6: learn: 0.6575295 test: 0.6573748 best: 0.6573748 (6) total: 1.78s remaining: 4m 12s
7: learn: 0.6530926 test: 0.6530158 best: 0.6530158 (7) total: 2.19s remaining: 4m 31s
8: learn: 0.6486140 test: 0.6485535 best: 0.6485535 (8) total: 2.56s remaining: 4m 42s
9: learn: 0.6440716 test: 0.6440460 best: 0.6440460 (9) total: 2.93s remaining: 4m 50s
10: learn: 0.6396833 test: 0.6395909 best: 0.6395909 (10) total: 3.13s remaining: 4m 41s
11: learn: 0.6351456 test: 0.6350678 best: 0.6350678 (11) total: 3.39s remaining: 4m 39s
12: learn: 0.6310688 test: 0.6309944 best: 0.6309944 (12) total: 3.53s remaining: 4m 27s
13: learn: 0.6268495 test: 0.6267702 best: 0.6267702 (13) total: 3.67s remaining: 4m 18s
14: learn: 0.6228036 test: 0.6227191 best: 0.6227191 (14) total: 4.06s remaining: 4m 26s
15: learn: 0.6190464 test: 0.6188843 best: 0.6188843 (15) total: 4.2s remaining: 4m 18s
16: learn: 0.6150497 test: 0.6149078 best: 0.6149078 (16) total: 4.59s remaining: 4m 25s
17: learn: 0.6113199 test: 0.6111696 best: 0.6111696 (17) total: 4.96s remaining: 4m 30s
18: learn: 0.6075876 test: 0.6074646 best: 0.6074646 (18) total: 5.32s remaining: 4m 34s
19: learn: 0.6039775 test: 0.6038067 best: 0.6038067 (19) total: 5.7s remaining: 4m 39s
20: learn: 0.6004446 test: 0.6003022 best: 0.6003022 (20) total: 6.09s remaining: 4m 43s
21: learn: 0.5970491 test: 0.5969205 best: 0.5969205 (21) total: 6.24s remaining: 4m 37s
22: learn: 0.5937698 test: 0.5936425 best: 0.5936425 (22) total: 6.35s remaining: 4m 29s
23: learn: 0.5905740 test: 0.5904508 best: 0.5904508 (23) total: 6.55s remaining: 4m 26s
24: learn: 0.5872053 test: 0.5871138 best: 0.5871138 (24) total: 6.96s remaining: 4m 31s
25: learn: 0.5840443 test: 0.5838871 best: 0.5838871 (25) total: 7.35s remaining: 4m 35s
26: learn: 0.5812196 test: 0.5810589 best: 0.5810589 (26) total: 7.44s remaining: 4m 28s
27: learn: 0.5784331 test: 0.5782633 best: 0.5782633 (27) total: 7.52s remaining: 4m 21s
28: learn: 0.5757943 test: 0.5755243 best: 0.5755243 (28) total: 7.64s remaining: 4m 15s
29: learn: 0.5728925 test: 0.5726308 best: 0.5726308 (29) total: 8.03s remaining: 4m 19s
30: learn: 0.5698602 test: 0.5695899 best: 0.5695899 (30) total: 8.47s remaining: 4m 24s
31: learn: 0.5670454 test: 0.5667457 best: 0.5667457 (31) total: 8.91s remaining: 4m 29s
32: learn: 0.5645590 test: 0.5642612 best: 0.5642612 (32) total: 8.97s remaining: 4m 22s
33: learn: 0.5618375 test: 0.5615256 best: 0.5615256 (33) total: 9.31s remaining: 4m 24s
34: learn: 0.5593598 test: 0.5590209 best: 0.5590209 (34) total: 9.63s remaining: 4m 25s
35: learn: 0.5568221 test: 0.5564812 best: 0.5564812 (35) total: 9.84s remaining: 4m 23s
36: learn: 0.5545868 test: 0.5541902 best: 0.5541902 (36) total: 10.1s remaining: 4m 21s
37: learn: 0.5524951 test: 0.5520953 best: 0.5520953 (37) total: 10.1s remaining: 4m 16s
38: learn: 0.5499668 test: 0.5495827 best: 0.5495827 (38) total: 10.5s remaining: 4m 18s
39: learn: 0.5476750 test: 0.5472995 best: 0.5472995 (39) total: 10.7s remaining: 4m 17s
40: learn: 0.5454425 test: 0.5450474 best: 0.5450474 (40) total: 11.1s remaining: 4m 19s
41: learn: 0.5433236 test: 0.5429331 best: 0.5429331 (41) total: 11.3s remaining: 4m 16s
42: learn: 0.5410224 test: 0.5406444 best: 0.5406444 (42) total: 11.6s remaining: 4m 18s
43: learn: 0.5391164 test: 0.5387519 best: 0.5387519 (43) total: 11.7s remaining: 4m 15s
44: learn: 0.5368752 test: 0.5365139 best: 0.5365139 (44) total: 12.1s remaining: 4m 16s
45: learn: 0.5346884 test: 0.5343396 best: 0.5343396 (45) total: 12.4s remaining: 4m 16s
46: learn: 0.5327126 test: 0.5323722 best: 0.5323722 (46) total: 12.5s remaining: 4m 13s
47: learn: 0.5306926 test: 0.5303511 best: 0.5303511 (47) total: 12.8s remaining: 4m 13s
48: learn: 0.5288586 test: 0.5284876 best: 0.5284876 (48) total: 12.9s remaining: 4m 10s
49: learn: 0.5273418 test: 0.5269585 best: 0.5269585 (49) total: 13s remaining: 4m 6s
50: learn: 0.5256582 test: 0.5252801 best: 0.5252801 (50) total: 13.1s remaining: 4m 3s
51: learn: 0.5238297 test: 0.5234549 best: 0.5234549 (51) total: 13.3s remaining: 4m 2s
52: learn: 0.5222664 test: 0.5218904 best: 0.5218904 (52) total: 13.4s remaining: 3m 59s
53: learn: 0.5203880 test: 0.5200059 best: 0.5200059 (53) total: 13.7s remaining: 4m
54: learn: 0.5187852 test: 0.5183779 best: 0.5183779 (54) total: 14.1s remaining: 4m 2s
55: learn: 0.5170896 test: 0.5166968 best: 0.5166968 (55) total: 14.5s remaining: 4m 4s
56: learn: 0.5155334 test: 0.5151275 best: 0.5151275 (56) total: 14.7s remaining: 4m 3s
57: learn: 0.5141501 test: 0.5137385 best: 0.5137385 (57) total: 14.9s remaining: 4m 2s
58: learn: 0.5125709 test: 0.5121552 best: 0.5121552 (58) total: 15.1s remaining: 4m
59: learn: 0.5112342 test: 0.5108025 best: 0.5108025 (59) total: 15.3s remaining: 3m 59s
60: learn: 0.5097859 test: 0.5093731 best: 0.5093731 (60) total: 15.4s remaining: 3m 57s
61: learn: 0.5083883 test: 0.5079757 best: 0.5079757 (61) total: 15.6s remaining: 3m 55s
62: learn: 0.5069173 test: 0.5065196 best: 0.5065196 (62) total: 15.9s remaining: 3m 56s
63: learn: 0.5056460 test: 0.5052465 best: 0.5052465 (63) total: 16.2s remaining: 3m 56s
64: learn: 0.5041283 test: 0.5037452 best: 0.5037452 (64) total: 16.5s remaining: 3m 57s
65: learn: 0.5027224 test: 0.5023235 best: 0.5023235 (65) total: 16.8s remaining: 3m 57s
66: learn: 0.5016726 test: 0.5012679 best: 0.5012679 (66) total: 16.8s remaining: 3m 54s
67: learn: 0.5003152 test: 0.4999222 best: 0.4999222 (67) total: 17.2s remaining: 3m 55s
68: learn: 0.4990399 test: 0.4986684 best: 0.4986684 (68) total: 17.4s remaining: 3m 55s
69: learn: 0.4980020 test: 0.4975950 best: 0.4975950 (69) total: 17.8s remaining: 3m 56s
70: learn: 0.4968073 test: 0.4964056 best: 0.4964056 (70) total: 18.2s remaining: 3m 57s
71: learn: 0.4956530 test: 0.4952554 best: 0.4952554 (71) total: 18.6s remaining: 3m 59s
72: learn: 0.4945539 test: 0.4941519 best: 0.4941519 (72) total: 18.9s remaining: 4m
73: learn: 0.4934179 test: 0.4930362 best: 0.4930362 (73) total: 19.3s remaining: 4m 1s
74: learn: 0.4923152 test: 0.4919602 best: 0.4919602 (74) total: 19.5s remaining: 4m
75: learn: 0.4914473 test: 0.4910903 best: 0.4910903 (75) total: 19.7s remaining: 3m 59s
76: learn: 0.4905832 test: 0.4902241 best: 0.4902241 (76) total: 19.8s remaining: 3m 57s
77: learn: 0.4895554 test: 0.4891888 best: 0.4891888 (77) total: 20s remaining: 3m 56s
78: learn: 0.4885145 test: 0.4881634 best: 0.4881634 (78) total: 20.4s remaining: 3m 58s
79: learn: 0.4876799 test: 0.4873318 best: 0.4873318 (79) total: 20.7s remaining: 3m 58s
80: learn: 0.4866471 test: 0.4863014 best: 0.4863014 (80) total: 21.1s remaining: 3m 59s
81: learn: 0.4856451 test: 0.4852965 best: 0.4852965 (81) total: 21.5s remaining: 4m
82: learn: 0.4847752 test: 0.4844269 best: 0.4844269 (82) total: 21.9s remaining: 4m 1s
83: learn: 0.4836890 test: 0.4833673 best: 0.4833673 (83) total: 22.3s remaining: 4m 3s
84: learn: 0.4827863 test: 0.4824705 best: 0.4824705 (84) total: 22.6s remaining: 4m 3s
85: learn: 0.4820386 test: 0.4817411 best: 0.4817411 (85) total: 22.8s remaining: 4m 2s
86: learn: 0.4811137 test: 0.4808457 best: 0.4808457 (86) total: 23.2s remaining: 4m 3s
87: learn: 0.4801362 test: 0.4798840 best: 0.4798840 (87) total: 23.7s remaining: 4m 5s
88: learn: 0.4792732 test: 0.4790452 best: 0.4790452 (88) total: 24.1s remaining: 4m 6s
89: learn: 0.4786035 test: 0.4783625 best: 0.4783625 (89) total: 24.2s remaining: 4m 4s
90: learn: 0.4777271 test: 0.4774667 best: 0.4774667 (90) total: 24.6s remaining: 4m 6s
91: learn: 0.4769086 test: 0.4766372 best: 0.4766372 (91) total: 25s remaining: 4m 6s
92: learn: 0.4760027 test: 0.4757477 best: 0.4757477 (92) total: 25.4s remaining: 4m 7s
93: learn: 0.4753141 test: 0.4750579 best: 0.4750579 (93) total: 25.6s remaining: 4m 6s
94: learn: 0.4746413 test: 0.4743904 best: 0.4743904 (94) total: 25.7s remaining: 4m 5s
95: learn: 0.4740408 test: 0.4737976 best: 0.4737976 (95) total: 25.9s remaining: 4m 3s
96: learn: 0.4733292 test: 0.4730864 best: 0.4730864 (96) total: 26.2s remaining: 4m 3s
97: learn: 0.4726834 test: 0.4724513 best: 0.4724513 (97) total: 26.4s remaining: 4m 2s
98: learn: 0.4719432 test: 0.4717310 best: 0.4717310 (98) total: 26.8s remaining: 4m 3s
99: learn: 0.4711617 test: 0.4709654 best: 0.4709654 (99) total: 27.1s remaining: 4m 4s
100: learn: 0.4706076 test: 0.4704319 best: 0.4704319 (100) total: 27.6s remaining: 4m 5s
101: learn: 0.4700848 test: 0.4699148 best: 0.4699148 (101) total: 27.7s remaining: 4m 3s
102: learn: 0.4695464 test: 0.4693823 best: 0.4693823 (102) total: 27.9s remaining: 4m 2s
103: learn: 0.4689858 test: 0.4688493 best: 0.4688493 (103) total: 28.3s remaining: 4m 4s
104: learn: 0.4683744 test: 0.4682385 best: 0.4682385 (104) total: 28.8s remaining: 4m 5s
105: learn: 0.4677182 test: 0.4676094 best: 0.4676094 (105) total: 29.2s remaining: 4m 5s
106: learn: 0.4673187 test: 0.4672108 best: 0.4672108 (106) total: 29.2s remaining: 4m 4s
107: learn: 0.4666856 test: 0.4666042 best: 0.4666042 (107) total: 29.7s remaining: 4m 5s
108: learn: 0.4660045 test: 0.4659417 best: 0.4659417 (108) total: 30.1s remaining: 4m 6s
109: learn: 0.4655279 test: 0.4654780 best: 0.4654780 (109) total: 30.6s remaining: 4m 7s
110: learn: 0.4650138 test: 0.4649572 best: 0.4649572 (110) total: 30.7s remaining: 4m 6s
111: learn: 0.4644346 test: 0.4643824 best: 0.4643824 (111) total: 31.1s remaining: 4m 6s
112: learn: 0.4639676 test: 0.4639147 best: 0.4639147 (112) total: 31.5s remaining: 4m 7s
113: learn: 0.4635754 test: 0.4635245 best: 0.4635245 (113) total: 31.7s remaining: 4m 6s
114: learn: 0.4631849 test: 0.4631339 best: 0.4631339 (114) total: 31.8s remaining: 4m 4s
115: learn: 0.4626820 test: 0.4626338 best: 0.4626338 (115) total: 32.2s remaining: 4m 5s
116: learn: 0.4622141 test: 0.4621710 best: 0.4621710 (116) total: 32.4s remaining: 4m 4s
117: learn: 0.4617183 test: 0.4617031 best: 0.4617031 (117) total: 32.8s remaining: 4m 5s
118: learn: 0.4613079 test: 0.4613025 best: 0.4613025 (118) total: 33.2s remaining: 4m 5s
119: learn: 0.4607222 test: 0.4607278 best: 0.4607278 (119) total: 33.6s remaining: 4m 6s
120: learn: 0.4601782 test: 0.4602156 best: 0.4602156 (120) total: 33.9s remaining: 4m 6s
121: learn: 0.4596441 test: 0.4596909 best: 0.4596909 (121) total: 34.3s remaining: 4m 6s
122: learn: 0.4591385 test: 0.4592089 best: 0.4592089 (122) total: 34.8s remaining: 4m 8s
123: learn: 0.4586400 test: 0.4587086 best: 0.4587086 (123) total: 35.3s remaining: 4m 9s
124: learn: 0.4581804 test: 0.4582726 best: 0.4582726 (124) total: 35.7s remaining: 4m 9s
125: learn: 0.4578162 test: 0.4579058 best: 0.4579058 (125) total: 35.9s remaining: 4m 8s
126: learn: 0.4574353 test: 0.4575341 best: 0.4575341 (126) total: 36.3s remaining: 4m 9s
127: learn: 0.4570118 test: 0.4571398 best: 0.4571398 (127) total: 36.7s remaining: 4m 10s
128: learn: 0.4566966 test: 0.4568234 best: 0.4568234 (128) total: 36.9s remaining: 4m 9s
129: learn: 0.4563426 test: 0.4564712 best: 0.4564712 (129) total: 37.1s remaining: 4m 8s
130: learn: 0.4560198 test: 0.4561676 best: 0.4561676 (130) total: 37.4s remaining: 4m 7s
131: learn: 0.4555712 test: 0.4557510 best: 0.4557510 (131) total: 37.7s remaining: 4m 8s
132: learn: 0.4552158 test: 0.4553926 best: 0.4553926 (132) total: 38.2s remaining: 4m 9s
133: learn: 0.4548658 test: 0.4550516 best: 0.4550516 (133) total: 38.6s remaining: 4m 9s
134: learn: 0.4545793 test: 0.4547590 best: 0.4547590 (134) total: 38.9s remaining: 4m 9s
135: learn: 0.4542879 test: 0.4544645 best: 0.4544645 (135) total: 39.1s remaining: 4m 8s
136: learn: 0.4539429 test: 0.4541179 best: 0.4541179 (136) total: 39.4s remaining: 4m 7s
137: learn: 0.4537165 test: 0.4538866 best: 0.4538866 (137) total: 39.4s remaining: 4m 6s
138: learn: 0.4533745 test: 0.4535755 best: 0.4535755 (138) total: 39.8s remaining: 4m 6s
139: learn: 0.4531032 test: 0.4533075 best: 0.4533075 (139) total: 39.9s remaining: 4m 5s
140: learn: 0.4527104 test: 0.4529196 best: 0.4529196 (140) total: 40.4s remaining: 4m 5s
141: learn: 0.4524196 test: 0.4526406 best: 0.4526406 (141) total: 40.7s remaining: 4m 6s
142: learn: 0.4520488 test: 0.4522843 best: 0.4522843 (142) total: 41.1s remaining: 4m 6s
143: learn: 0.4517971 test: 0.4520374 best: 0.4520374 (143) total: 41.6s remaining: 4m 7s
144: learn: 0.4515071 test: 0.4517590 best: 0.4517590 (144) total: 41.9s remaining: 4m 6s
145: learn: 0.4511591 test: 0.4513925 best: 0.4513925 (145) total: 42.2s remaining: 4m 6s
146: learn: 0.4509340 test: 0.4511773 best: 0.4511773 (146) total: 42.4s remaining: 4m 5s
147: learn: 0.4507469 test: 0.4509864 best: 0.4509864 (147) total: 42.5s remaining: 4m 4s
148: learn: 0.4505325 test: 0.4507705 best: 0.4507705 (148) total: 42.7s remaining: 4m 3s
149: learn: 0.4502787 test: 0.4505238 best: 0.4505238 (149) total: 42.9s remaining: 4m 3s
150: learn: 0.4499834 test: 0.4502454 best: 0.4502454 (150) total: 43.4s remaining: 4m 3s
151: learn: 0.4497428 test: 0.4500286 best: 0.4500286 (151) total: 43.8s remaining: 4m 4s
152: learn: 0.4495144 test: 0.4498030 best: 0.4498030 (152) total: 44s remaining: 4m 3s
153: learn: 0.4492192 test: 0.4495148 best: 0.4495148 (153) total: 44.5s remaining: 4m 4s
154: learn: 0.4488630 test: 0.4491652 best: 0.4491652 (154) total: 44.9s remaining: 4m 4s
155: learn: 0.4486301 test: 0.4489373 best: 0.4489373 (155) total: 45s remaining: 4m 3s
156: learn: 0.4483591 test: 0.4487103 best: 0.4487103 (156) total: 45.5s remaining: 4m 4s
157: learn: 0.4481237 test: 0.4484880 best: 0.4484880 (157) total: 45.8s remaining: 4m 4s
158: learn: 0.4478932 test: 0.4482617 best: 0.4482617 (158) total: 46.3s remaining: 4m 4s
159: learn: 0.4476553 test: 0.4480259 best: 0.4480259 (159) total: 46.5s remaining: 4m 4s
160: learn: 0.4473948 test: 0.4477836 best: 0.4477836 (160) total: 46.9s remaining: 4m 4s
161: learn: 0.4471267 test: 0.4475200 best: 0.4475200 (161) total: 47.4s remaining: 4m 5s
162: learn: 0.4469570 test: 0.4473515 best: 0.4473515 (162) total: 47.7s remaining: 4m 4s
163: learn: 0.4467281 test: 0.4471271 best: 0.4471271 (163) total: 47.9s remaining: 4m 4s
164: learn: 0.4465371 test: 0.4469327 best: 0.4469327 (164) total: 48.1s remaining: 4m 3s
165: learn: 0.4462952 test: 0.4467199 best: 0.4467199 (165) total: 48.4s remaining: 4m 3s
166: learn: 0.4460426 test: 0.4464750 best: 0.4464750 (166) total: 48.9s remaining: 4m 4s
167: learn: 0.4458067 test: 0.4462497 best: 0.4462497 (167) total: 49.2s remaining: 4m 3s
168: learn: 0.4455490 test: 0.4460044 best: 0.4460044 (168) total: 49.7s remaining: 4m 4s
169: learn: 0.4453874 test: 0.4458377 best: 0.4458377 (169) total: 50s remaining: 4m 4s
170: learn: 0.4451453 test: 0.4455947 best: 0.4455947 (170) total: 50.5s remaining: 4m 5s
171: learn: 0.4449051 test: 0.4453510 best: 0.4453510 (171) total: 51.1s remaining: 4m 5s
172: learn: 0.4447259 test: 0.4451763 best: 0.4451763 (172) total: 51.6s remaining: 4m 6s
173: learn: 0.4444845 test: 0.4449515 best: 0.4449515 (173) total: 52.1s remaining: 4m 7s
174: learn: 0.4442510 test: 0.4447299 best: 0.4447299 (174) total: 52.6s remaining: 4m 8s
175: learn: 0.4440307 test: 0.4445285 best: 0.4445285 (175) total: 53.1s remaining: 4m 8s
176: learn: 0.4437481 test: 0.4442636 best: 0.4442636 (176) total: 53.6s remaining: 4m 9s
177: learn: 0.4435282 test: 0.4440394 best: 0.4440394 (177) total: 54.1s remaining: 4m 9s
178: learn: 0.4433260 test: 0.4438373 best: 0.4438373 (178) total: 54.5s remaining: 4m 9s
179: learn: 0.4431671 test: 0.4436880 best: 0.4436880 (179) total: 55s remaining: 4m 10s
180: learn: 0.4429813 test: 0.4435128 best: 0.4435128 (180) total: 55.4s remaining: 4m 10s
181: learn: 0.4427715 test: 0.4433132 best: 0.4433132 (181) total: 55.9s remaining: 4m 11s
182: learn: 0.4425937 test: 0.4431455 best: 0.4431455 (182) total: 56.2s remaining: 4m 10s
183: learn: 0.4423872 test: 0.4429809 best: 0.4429809 (183) total: 56.6s remaining: 4m 11s
184: learn: 0.4422281 test: 0.4428354 best: 0.4428354 (184) total: 57.1s remaining: 4m 11s
185: learn: 0.4420779 test: 0.4427036 best: 0.4427036 (185) total: 57.4s remaining: 4m 11s
186: learn: 0.4419770 test: 0.4426062 best: 0.4426062 (186) total: 57.6s remaining: 4m 10s
187: learn: 0.4417953 test: 0.4424418 best: 0.4424418 (187) total: 58.1s remaining: 4m 10s
188: learn: 0.4416095 test: 0.4422800 best: 0.4422800 (188) total: 58.5s remaining: 4m 11s
189: learn: 0.4414157 test: 0.4420853 best: 0.4420853 (189) total: 58.9s remaining: 4m 10s
190: learn: 0.4412573 test: 0.4419307 best: 0.4419307 (190) total: 59.3s remaining: 4m 11s
191: learn: 0.4411220 test: 0.4418057 best: 0.4418057 (191) total: 59.5s remaining: 4m 10s
192: learn: 0.4410290 test: 0.4417068 best: 0.4417068 (192) total: 59.6s remaining: 4m 9s
193: learn: 0.4409378 test: 0.4416220 best: 0.4416220 (193) total: 59.8s remaining: 4m 8s
194: learn: 0.4407424 test: 0.4414340 best: 0.4414340 (194) total: 1m remaining: 4m 8s
195: learn: 0.4406122 test: 0.4413153 best: 0.4413153 (195) total: 1m remaining: 4m 7s
196: learn: 0.4404608 test: 0.4411822 best: 0.4411822 (196) total: 1m remaining: 4m 8s
197: learn: 0.4403738 test: 0.4410911 best: 0.4410911 (197) total: 1m 1s remaining: 4m 7s
198: learn: 0.4401774 test: 0.4409198 best: 0.4409198 (198) total: 1m 1s remaining: 4m 7s
199: learn: 0.4400341 test: 0.4407915 best: 0.4407915 (199) total: 1m 1s remaining: 4m 7s
200: learn: 0.4399007 test: 0.4406589 best: 0.4406589 (200) total: 1m 2s remaining: 4m 6s
201: learn: 0.4397775 test: 0.4405336 best: 0.4405336 (201) total: 1m 2s remaining: 4m 5s
202: learn: 0.4396342 test: 0.4403905 best: 0.4403905 (202) total: 1m 2s remaining: 4m 6s
203: learn: 0.4394853 test: 0.4402552 best: 0.4402552 (203) total: 1m 3s remaining: 4m 6s
204: learn: 0.4393554 test: 0.4401466 best: 0.4401466 (204) total: 1m 3s remaining: 4m 6s
205: learn: 0.4391913 test: 0.4399832 best: 0.4399832 (205) total: 1m 4s remaining: 4m 6s
206: learn: 0.4391069 test: 0.4398986 best: 0.4398986 (206) total: 1m 4s remaining: 4m 6s
207: learn: 0.4389886 test: 0.4397811 best: 0.4397811 (207) total: 1m 4s remaining: 4m 6s
208: learn: 0.4388975 test: 0.4396943 best: 0.4396943 (208) total: 1m 4s remaining: 4m 5s
209: learn: 0.4388215 test: 0.4396207 best: 0.4396207 (209) total: 1m 5s remaining: 4m 4s
210: learn: 0.4386652 test: 0.4394802 best: 0.4394802 (210) total: 1m 5s remaining: 4m 5s
211: learn: 0.4385048 test: 0.4393472 best: 0.4393472 (211) total: 1m 6s remaining: 4m 5s
212: learn: 0.4383891 test: 0.4392492 best: 0.4392492 (212) total: 1m 6s remaining: 4m 5s
213: learn: 0.4382900 test: 0.4391540 best: 0.4391540 (213) total: 1m 6s remaining: 4m 5s
214: learn: 0.4381708 test: 0.4390421 best: 0.4390421 (214) total: 1m 7s remaining: 4m 4s
215: learn: 0.4380261 test: 0.4389069 best: 0.4389069 (215) total: 1m 7s remaining: 4m 5s
216: learn: 0.4379545 test: 0.4388292 best: 0.4388292 (216) total: 1m 7s remaining: 4m 4s
217: learn: 0.4378844 test: 0.4387566 best: 0.4387566 (217) total: 1m 7s remaining: 4m 3s
218: learn: 0.4377599 test: 0.4386595 best: 0.4386595 (218) total: 1m 8s remaining: 4m 3s
219: learn: 0.4376183 test: 0.4385183 best: 0.4385183 (219) total: 1m 8s remaining: 4m 3s
220: learn: 0.4375222 test: 0.4384295 best: 0.4384295 (220) total: 1m 9s remaining: 4m 3s
221: learn: 0.4374263 test: 0.4383432 best: 0.4383432 (221) total: 1m 9s remaining: 4m 3s
222: learn: 0.4373288 test: 0.4382571 best: 0.4382571 (222) total: 1m 9s remaining: 4m 2s
223: learn: 0.4372230 test: 0.4381620 best: 0.4381620 (223) total: 1m 9s remaining: 4m 2s
224: learn: 0.4370743 test: 0.4380264 best: 0.4380264 (224) total: 1m 10s remaining: 4m 2s
225: learn: 0.4369983 test: 0.4379408 best: 0.4379408 (225) total: 1m 10s remaining: 4m 2s
226: learn: 0.4369167 test: 0.4378574 best: 0.4378574 (226) total: 1m 10s remaining: 4m 1s
227: learn: 0.4367960 test: 0.4377674 best: 0.4377674 (227) total: 1m 11s remaining: 4m 1s
228: learn: 0.4366626 test: 0.4376495 best: 0.4376495 (228) total: 1m 11s remaining: 4m 2s
229: learn: 0.4365534 test: 0.4375677 best: 0.4375677 (229) total: 1m 12s remaining: 4m 1s
230: learn: 0.4364079 test: 0.4374393 best: 0.4374393 (230) total: 1m 12s remaining: 4m 1s
231: learn: 0.4363215 test: 0.4373636 best: 0.4373636 (231) total: 1m 12s remaining: 4m 1s
232: learn: 0.4361744 test: 0.4372337 best: 0.4372337 (232) total: 1m 13s remaining: 4m 1s
233: learn: 0.4360742 test: 0.4371590 best: 0.4371590 (233) total: 1m 13s remaining: 4m 1s
234: learn: 0.4360309 test: 0.4371136 best: 0.4371136 (234) total: 1m 13s remaining: 4m
235: learn: 0.4359074 test: 0.4370214 best: 0.4370214 (235) total: 1m 14s remaining: 4m
236: learn: 0.4358066 test: 0.4369414 best: 0.4369414 (236) total: 1m 14s remaining: 4m
237: learn: 0.4356523 test: 0.4368157 best: 0.4368157 (237) total: 1m 15s remaining: 4m 1s
238: learn: 0.4355625 test: 0.4367496 best: 0.4367496 (238) total: 1m 15s remaining: 4m
239: learn: 0.4354446 test: 0.4366538 best: 0.4366538 (239) total: 1m 16s remaining: 4m
240: learn: 0.4353602 test: 0.4365871 best: 0.4365871 (240) total: 1m 16s remaining: 4m 1s
241: learn: 0.4352535 test: 0.4364943 best: 0.4364943 (241) total: 1m 16s remaining: 4m
242: learn: 0.4351368 test: 0.4363679 best: 0.4363679 (242) total: 1m 17s remaining: 4m
243: learn: 0.4350620 test: 0.4363152 best: 0.4363152 (243) total: 1m 17s remaining: 4m
244: learn: 0.4349576 test: 0.4362141 best: 0.4362141 (244) total: 1m 18s remaining: 4m
245: learn: 0.4348343 test: 0.4361199 best: 0.4361199 (245) total: 1m 18s remaining: 4m
246: learn: 0.4347635 test: 0.4360646 best: 0.4360646 (246) total: 1m 18s remaining: 4m
247: learn: 0.4346283 test: 0.4359496 best: 0.4359496 (247) total: 1m 19s remaining: 4m
248: learn: 0.4345248 test: 0.4358717 best: 0.4358717 (248) total: 1m 19s remaining: 4m
249: learn: 0.4344238 test: 0.4357876 best: 0.4357876 (249) total: 1m 20s remaining: 4m
250: learn: 0.4343181 test: 0.4356994 best: 0.4356994 (250) total: 1m 20s remaining: 4m
251: learn: 0.4342424 test: 0.4356370 best: 0.4356370 (251) total: 1m 20s remaining: 4m
252: learn: 0.4341814 test: 0.4355651 best: 0.4355651 (252) total: 1m 21s remaining: 3m 59s
253: learn: 0.4340958 test: 0.4354831 best: 0.4354831 (253) total: 1m 21s remaining: 3m 59s
254: learn: 0.4340105 test: 0.4354115 best: 0.4354115 (254) total: 1m 21s remaining: 3m 59s
255: learn: 0.4339579 test: 0.4353697 best: 0.4353697 (255) total: 1m 22s remaining: 3m 58s
256: learn: 0.4338546 test: 0.4352841 best: 0.4352841 (256) total: 1m 22s remaining: 3m 58s
257: learn: 0.4337588 test: 0.4352025 best: 0.4352025 (257) total: 1m 23s remaining: 3m 58s
258: learn: 0.4336687 test: 0.4351209 best: 0.4351209 (258) total: 1m 23s remaining: 3m 59s
259: learn: 0.4336178 test: 0.4350721 best: 0.4350721 (259) total: 1m 23s remaining: 3m 58s
260: learn: 0.4335120 test: 0.4349912 best: 0.4349912 (260) total: 1m 24s remaining: 3m 58s
261: learn: 0.4334036 test: 0.4349006 best: 0.4349006 (261) total: 1m 24s remaining: 3m 58s
262: learn: 0.4333133 test: 0.4348476 best: 0.4348476 (262) total: 1m 25s remaining: 3m 58s
263: learn: 0.4332327 test: 0.4347773 best: 0.4347773 (263) total: 1m 25s remaining: 3m 58s
264: learn: 0.4331243 test: 0.4347049 best: 0.4347049 (264) total: 1m 25s remaining: 3m 58s
265: learn: 0.4330196 test: 0.4346212 best: 0.4346212 (265) total: 1m 26s remaining: 3m 58s
266: learn: 0.4329124 test: 0.4345467 best: 0.4345467 (266) total: 1m 26s remaining: 3m 58s
267: learn: 0.4328481 test: 0.4344854 best: 0.4344854 (267) total: 1m 27s remaining: 3m 58s
268: learn: 0.4327700 test: 0.4344203 best: 0.4344203 (268) total: 1m 27s remaining: 3m 58s
269: learn: 0.4327285 test: 0.4343890 best: 0.4343890 (269) total: 1m 28s remaining: 3m 57s
270: learn: 0.4326398 test: 0.4343085 best: 0.4343085 (270) total: 1m 28s remaining: 3m 57s
271: learn: 0.4325576 test: 0.4342499 best: 0.4342499 (271) total: 1m 28s remaining: 3m 58s
272: learn: 0.4324511 test: 0.4341358 best: 0.4341358 (272) total: 1m 29s remaining: 3m 58s
273: learn: 0.4324107 test: 0.4340821 best: 0.4340821 (273) total: 1m 29s remaining: 3m 57s
274: learn: 0.4323526 test: 0.4340311 best: 0.4340311 (274) total: 1m 30s remaining: 3m 57s
275: learn: 0.4322802 test: 0.4339775 best: 0.4339775 (275) total: 1m 30s remaining: 3m 57s
276: learn: 0.4321911 test: 0.4339178 best: 0.4339178 (276) total: 1m 31s remaining: 3m 57s
277: learn: 0.4321339 test: 0.4338693 best: 0.4338693 (277) total: 1m 31s remaining: 3m 57s
278: learn: 0.4320924 test: 0.4338293 best: 0.4338293 (278) total: 1m 31s remaining: 3m 56s
279: learn: 0.4319772 test: 0.4337691 best: 0.4337691 (279) total: 1m 32s remaining: 3m 57s
280: learn: 0.4319226 test: 0.4337255 best: 0.4337255 (280) total: 1m 32s remaining: 3m 57s
281: learn: 0.4318416 test: 0.4336523 best: 0.4336523 (281) total: 1m 33s remaining: 3m 57s
282: learn: 0.4317427 test: 0.4335624 best: 0.4335624 (282) total: 1m 33s remaining: 3m 57s
283: learn: 0.4316738 test: 0.4335074 best: 0.4335074 (283) total: 1m 34s remaining: 3m 57s
284: learn: 0.4316119 test: 0.4334653 best: 0.4334653 (284) total: 1m 34s remaining: 3m 57s
285: learn: 0.4315504 test: 0.4334112 best: 0.4334112 (285) total: 1m 35s remaining: 3m 57s
286: learn: 0.4314923 test: 0.4333689 best: 0.4333689 (286) total: 1m 35s remaining: 3m 57s
287: learn: 0.4313797 test: 0.4332840 best: 0.4332840 (287) total: 1m 35s remaining: 3m 57s
288: learn: 0.4313140 test: 0.4332232 best: 0.4332232 (288) total: 1m 36s remaining: 3m 56s
289: learn: 0.4312616 test: 0.4331700 best: 0.4331700 (289) total: 1m 36s remaining: 3m 55s
290: learn: 0.4311689 test: 0.4331100 best: 0.4331100 (290) total: 1m 36s remaining: 3m 55s
291: learn: 0.4311362 test: 0.4330773 best: 0.4330773 (291) total: 1m 37s remaining: 3m 55s
292: learn: 0.4310727 test: 0.4330191 best: 0.4330191 (292) total: 1m 37s remaining: 3m 54s
293: learn: 0.4309928 test: 0.4329458 best: 0.4329458 (293) total: 1m 37s remaining: 3m 54s
294: learn: 0.4309089 test: 0.4328776 best: 0.4328776 (294) total: 1m 38s remaining: 3m 54s
295: learn: 0.4308367 test: 0.4328245 best: 0.4328245 (295) total: 1m 38s remaining: 3m 54s
296: learn: 0.4307687 test: 0.4327711 best: 0.4327711 (296) total: 1m 39s remaining: 3m 54s
297: learn: 0.4307117 test: 0.4327204 best: 0.4327204 (297) total: 1m 39s remaining: 3m 54s
298: learn: 0.4306760 test: 0.4326866 best: 0.4326866 (298) total: 1m 39s remaining: 3m 53s
299: learn: 0.4306313 test: 0.4326394 best: 0.4326394 (299) total: 1m 39s remaining: 3m 52s
300: learn: 0.4305780 test: 0.4325933 best: 0.4325933 (300) total: 1m 40s remaining: 3m 52s
301: learn: 0.4304875 test: 0.4325275 best: 0.4325275 (301) total: 1m 40s remaining: 3m 52s
302: learn: 0.4304098 test: 0.4324689 best: 0.4324689 (302) total: 1m 41s remaining: 3m 52s
303: learn: 0.4303561 test: 0.4324267 best: 0.4324267 (303) total: 1m 41s remaining: 3m 52s
304: learn: 0.4302991 test: 0.4323830 best: 0.4323830 (304) total: 1m 42s remaining: 3m 52s
305: learn: 0.4302230 test: 0.4323164 best: 0.4323164 (305) total: 1m 42s remaining: 3m 52s
306: learn: 0.4301916 test: 0.4322794 best: 0.4322794 (306) total: 1m 42s remaining: 3m 52s
307: learn: 0.4301306 test: 0.4322198 best: 0.4322198 (307) total: 1m 43s remaining: 3m 52s
308: learn: 0.4300635 test: 0.4321714 best: 0.4321714 (308) total: 1m 43s remaining: 3m 52s
309: learn: 0.4299745 test: 0.4321233 best: 0.4321233 (309) total: 1m 44s remaining: 3m 52s
310: learn: 0.4299479 test: 0.4321062 best: 0.4321062 (310) total: 1m 44s remaining: 3m 51s
311: learn: 0.4298828 test: 0.4320588 best: 0.4320588 (311) total: 1m 44s remaining: 3m 51s
312: learn: 0.4297949 test: 0.4319731 best: 0.4319731 (312) total: 1m 45s remaining: 3m 51s
313: learn: 0.4297273 test: 0.4319143 best: 0.4319143 (313) total: 1m 45s remaining: 3m 51s
314: learn: 0.4296823 test: 0.4318717 best: 0.4318717 (314) total: 1m 46s remaining: 3m 50s
315: learn: 0.4296093 test: 0.4318180 best: 0.4318180 (315) total: 1m 46s remaining: 3m 51s
316: learn: 0.4295690 test: 0.4317864 best: 0.4317864 (316) total: 1m 47s remaining: 3m 50s
317: learn: 0.4295204 test: 0.4317436 best: 0.4317436 (317) total: 1m 47s remaining: 3m 50s
318: learn: 0.4294647 test: 0.4316985 best: 0.4316985 (318) total: 1m 47s remaining: 3m 50s
319: learn: 0.4294326 test: 0.4316783 best: 0.4316783 (319) total: 1m 48s remaining: 3m 49s
320: learn: 0.4293655 test: 0.4316201 best: 0.4316201 (320) total: 1m 48s remaining: 3m 49s
321: learn: 0.4293176 test: 0.4315768 best: 0.4315768 (321) total: 1m 48s remaining: 3m 49s
322: learn: 0.4291982 test: 0.4315106 best: 0.4315106 (322) total: 1m 49s remaining: 3m 49s
323: learn: 0.4291313 test: 0.4314684 best: 0.4314684 (323) total: 1m 49s remaining: 3m 49s
324: learn: 0.4290879 test: 0.4314385 best: 0.4314385 (324) total: 1m 50s remaining: 3m 49s
325: learn: 0.4290370 test: 0.4313939 best: 0.4313939 (325) total: 1m 50s remaining: 3m 48s
326: learn: 0.4290130 test: 0.4313730 best: 0.4313730 (326) total: 1m 50s remaining: 3m 48s
327: learn: 0.4289621 test: 0.4313376 best: 0.4313376 (327) total: 1m 51s remaining: 3m 48s
328: learn: 0.4288881 test: 0.4312875 best: 0.4312875 (328) total: 1m 51s remaining: 3m 48s
329: learn: 0.4288476 test: 0.4312517 best: 0.4312517 (329) total: 1m 52s remaining: 3m 48s
330: learn: 0.4287971 test: 0.4312183 best: 0.4312183 (330) total: 1m 52s remaining: 3m 47s
331: learn: 0.4287368 test: 0.4311703 best: 0.4311703 (331) total: 1m 53s remaining: 3m 47s
332: learn: 0.4286848 test: 0.4311287 best: 0.4311287 (332) total: 1m 53s remaining: 3m 47s
333: learn: 0.4286294 test: 0.4310895 best: 0.4310895 (333) total: 1m 53s remaining: 3m 47s
334: learn: 0.4285768 test: 0.4310587 best: 0.4310587 (334) total: 1m 54s remaining: 3m 47s
335: learn: 0.4285300 test: 0.4310159 best: 0.4310159 (335) total: 1m 54s remaining: 3m 46s
336: learn: 0.4284931 test: 0.4309833 best: 0.4309833 (336) total: 1m 54s remaining: 3m 46s
337: learn: 0.4284565 test: 0.4309548 best: 0.4309548 (337) total: 1m 55s remaining: 3m 45s
338: learn: 0.4283711 test: 0.4309106 best: 0.4309106 (338) total: 1m 55s remaining: 3m 45s
339: learn: 0.4282943 test: 0.4308521 best: 0.4308521 (339) total: 1m 56s remaining: 3m 45s
340: learn: 0.4282802 test: 0.4308383 best: 0.4308383 (340) total: 1m 56s remaining: 3m 44s
341: learn: 0.4282560 test: 0.4308193 best: 0.4308193 (341) total: 1m 56s remaining: 3m 44s
342: learn: 0.4282330 test: 0.4307996 best: 0.4307996 (342) total: 1m 56s remaining: 3m 43s
343: learn: 0.4282135 test: 0.4307859 best: 0.4307859 (343) total: 1m 56s remaining: 3m 42s
344: learn: 0.4281926 test: 0.4307730 best: 0.4307730 (344) total: 1m 57s remaining: 3m 42s
345: learn: 0.4281012 test: 0.4307325 best: 0.4307325 (345) total: 1m 57s remaining: 3m 42s
346: learn: 0.4280419 test: 0.4306967 best: 0.4306967 (346) total: 1m 58s remaining: 3m 42s
347: learn: 0.4279884 test: 0.4306752 best: 0.4306752 (347) total: 1m 58s remaining: 3m 42s
348: learn: 0.4279408 test: 0.4306318 best: 0.4306318 (348) total: 1m 59s remaining: 3m 42s
349: learn: 0.4278899 test: 0.4306105 best: 0.4306105 (349) total: 1m 59s remaining: 3m 41s
350: learn: 0.4278416 test: 0.4305702 best: 0.4305702 (350) total: 1m 59s remaining: 3m 41s
351: learn: 0.4277690 test: 0.4305175 best: 0.4305175 (351) total: 2m remaining: 3m 41s
352: learn: 0.4277009 test: 0.4304845 best: 0.4304845 (352) total: 2m remaining: 3m 41s
353: learn: 0.4276714 test: 0.4304595 best: 0.4304595 (353) total: 2m remaining: 3m 40s
354: learn: 0.4276027 test: 0.4304096 best: 0.4304096 (354) total: 2m 1s remaining: 3m 40s
355: learn: 0.4275309 test: 0.4303394 best: 0.4303394 (355) total: 2m 1s remaining: 3m 40s
356: learn: 0.4274802 test: 0.4303058 best: 0.4303058 (356) total: 2m 2s remaining: 3m 39s
357: learn: 0.4274350 test: 0.4302752 best: 0.4302752 (357) total: 2m 2s remaining: 3m 39s
358: learn: 0.4273334 test: 0.4302231 best: 0.4302231 (358) total: 2m 3s remaining: 3m 39s
359: learn: 0.4272705 test: 0.4301746 best: 0.4301746 (359) total: 2m 3s remaining: 3m 39s
360: learn: 0.4271770 test: 0.4301071 best: 0.4301071 (360) total: 2m 3s remaining: 3m 39s
361: learn: 0.4271318 test: 0.4300744 best: 0.4300744 (361) total: 2m 4s remaining: 3m 38s
362: learn: 0.4270717 test: 0.4300264 best: 0.4300264 (362) total: 2m 4s remaining: 3m 38s
363: learn: 0.4270080 test: 0.4299963 best: 0.4299963 (363) total: 2m 5s remaining: 3m 38s
364: learn: 0.4269850 test: 0.4299706 best: 0.4299706 (364) total: 2m 5s remaining: 3m 38s
365: learn: 0.4269692 test: 0.4299526 best: 0.4299526 (365) total: 2m 5s remaining: 3m 37s
366: learn: 0.4269453 test: 0.4299276 best: 0.4299276 (366) total: 2m 5s remaining: 3m 37s
367: learn: 0.4269166 test: 0.4299140 best: 0.4299140 (367) total: 2m 6s remaining: 3m 36s
368: learn: 0.4268925 test: 0.4298984 best: 0.4298984 (368) total: 2m 6s remaining: 3m 36s
369: learn: 0.4268365 test: 0.4298563 best: 0.4298563 (369) total: 2m 6s remaining: 3m 35s
370: learn: 0.4267759 test: 0.4298314 best: 0.4298314 (370) total: 2m 7s remaining: 3m 35s
371: learn: 0.4267432 test: 0.4297971 best: 0.4297971 (371) total: 2m 7s remaining: 3m 35s
372: learn: 0.4266611 test: 0.4297470 best: 0.4297470 (372) total: 2m 8s remaining: 3m 35s
373: learn: 0.4266507 test: 0.4297388 best: 0.4297388 (373) total: 2m 8s remaining: 3m 34s
374: learn: 0.4266067 test: 0.4297230 best: 0.4297230 (374) total: 2m 8s remaining: 3m 34s
375: learn: 0.4265460 test: 0.4296907 best: 0.4296907 (375) total: 2m 8s remaining: 3m 34s
376: learn: 0.4265154 test: 0.4296655 best: 0.4296655 (376) total: 2m 9s remaining: 3m 33s
377: learn: 0.4264885 test: 0.4296422 best: 0.4296422 (377) total: 2m 9s remaining: 3m 33s
378: learn: 0.4264286 test: 0.4295863 best: 0.4295863 (378) total: 2m 9s remaining: 3m 32s
379: learn: 0.4263532 test: 0.4295530 best: 0.4295530 (379) total: 2m 10s remaining: 3m 32s
380: learn: 0.4263146 test: 0.4295159 best: 0.4295159 (380) total: 2m 10s remaining: 3m 32s
381: learn: 0.4262541 test: 0.4294662 best: 0.4294662 (381) total: 2m 11s remaining: 3m 32s
382: learn: 0.4261709 test: 0.4294063 best: 0.4294063 (382) total: 2m 11s remaining: 3m 32s
383: learn: 0.4261204 test: 0.4293680 best: 0.4293680 (383) total: 2m 12s remaining: 3m 32s
384: learn: 0.4260533 test: 0.4293375 best: 0.4293375 (384) total: 2m 12s remaining: 3m 32s
385: learn: 0.4260196 test: 0.4293239 best: 0.4293239 (385) total: 2m 13s remaining: 3m 31s
386: learn: 0.4259354 test: 0.4292840 best: 0.4292840 (386) total: 2m 13s remaining: 3m 31s
387: learn: 0.4258712 test: 0.4292474 best: 0.4292474 (387) total: 2m 14s remaining: 3m 31s
388: learn: 0.4258226 test: 0.4292165 best: 0.4292165 (388) total: 2m 14s remaining: 3m 31s
389: learn: 0.4258118 test: 0.4292058 best: 0.4292058 (389) total: 2m 14s remaining: 3m 31s
390: learn: 0.4257698 test: 0.4291807 best: 0.4291807 (390) total: 2m 15s remaining: 3m 30s
391: learn: 0.4257629 test: 0.4291749 best: 0.4291749 (391) total: 2m 15s remaining: 3m 30s
392: learn: 0.4257329 test: 0.4291499 best: 0.4291499 (392) total: 2m 16s remaining: 3m 30s
393: learn: 0.4256894 test: 0.4291264 best: 0.4291264 (393) total: 2m 16s remaining: 3m 30s
394: learn: 0.4256494 test: 0.4290947 best: 0.4290947 (394) total: 2m 17s remaining: 3m 29s
395: learn: 0.4255712 test: 0.4290393 best: 0.4290393 (395) total: 2m 17s remaining: 3m 29s
396: learn: 0.4255265 test: 0.4290125 best: 0.4290125 (396) total: 2m 17s remaining: 3m 29s
397: learn: 0.4254743 test: 0.4289761 best: 0.4289761 (397) total: 2m 18s remaining: 3m 29s
398: learn: 0.4254551 test: 0.4289539 best: 0.4289539 (398) total: 2m 18s remaining: 3m 28s
399: learn: 0.4253884 test: 0.4289276 best: 0.4289276 (399) total: 2m 19s remaining: 3m 28s
400: learn: 0.4253275 test: 0.4288978 best: 0.4288978 (400) total: 2m 19s remaining: 3m 28s
401: learn: 0.4252822 test: 0.4288800 best: 0.4288800 (401) total: 2m 20s remaining: 3m 28s
402: learn: 0.4252644 test: 0.4288628 best: 0.4288628 (402) total: 2m 20s remaining: 3m 27s
403: learn: 0.4252087 test: 0.4288362 best: 0.4288362 (403) total: 2m 20s remaining: 3m 27s
404: learn: 0.4251627 test: 0.4288263 best: 0.4288263 (404) total: 2m 21s remaining: 3m 27s
405: learn: 0.4251225 test: 0.4288148 best: 0.4288148 (405) total: 2m 21s remaining: 3m 26s
406: learn: 0.4250800 test: 0.4287932 best: 0.4287932 (406) total: 2m 21s remaining: 3m 26s
407: learn: 0.4250465 test: 0.4287626 best: 0.4287626 (407) total: 2m 22s remaining: 3m 26s
408: learn: 0.4249933 test: 0.4287403 best: 0.4287403 (408) total: 2m 22s remaining: 3m 26s
409: learn: 0.4249484 test: 0.4287084 best: 0.4287084 (409) total: 2m 23s remaining: 3m 26s
410: learn: 0.4249278 test: 0.4286915 best: 0.4286915 (410) total: 2m 23s remaining: 3m 25s
411: learn: 0.4248909 test: 0.4286792 best: 0.4286792 (411) total: 2m 23s remaining: 3m 25s
412: learn: 0.4248679 test: 0.4286598 best: 0.4286598 (412) total: 2m 24s remaining: 3m 24s
413: learn: 0.4248412 test: 0.4286272 best: 0.4286272 (413) total: 2m 24s remaining: 3m 24s
414: learn: 0.4247920 test: 0.4286024 best: 0.4286024 (414) total: 2m 24s remaining: 3m 24s
415: learn: 0.4247866 test: 0.4285985 best: 0.4285985 (415) total: 2m 25s remaining: 3m 23s
416: learn: 0.4247581 test: 0.4285721 best: 0.4285721 (416) total: 2m 25s remaining: 3m 23s
417: learn: 0.4247171 test: 0.4285464 best: 0.4285464 (417) total: 2m 25s remaining: 3m 23s
418: learn: 0.4246823 test: 0.4285170 best: 0.4285170 (418) total: 2m 26s remaining: 3m 22s
419: learn: 0.4246694 test: 0.4285041 best: 0.4285041 (419) total: 2m 26s remaining: 3m 22s
420: learn: 0.4245963 test: 0.4284489 best: 0.4284489 (420) total: 2m 26s remaining: 3m 22s
421: learn: 0.4245685 test: 0.4284258 best: 0.4284258 (421) total: 2m 27s remaining: 3m 21s
422: learn: 0.4245278 test: 0.4283995 best: 0.4283995 (422) total: 2m 27s remaining: 3m 21s
423: learn: 0.4244971 test: 0.4283754 best: 0.4283754 (423) total: 2m 28s remaining: 3m 21s
424: learn: 0.4244766 test: 0.4283588 best: 0.4283588 (424) total: 2m 28s remaining: 3m 20s
425: learn: 0.4244188 test: 0.4283442 best: 0.4283442 (425) total: 2m 28s remaining: 3m 20s
426: learn: 0.4244137 test: 0.4283394 best: 0.4283394 (426) total: 2m 29s remaining: 3m 20s
427: learn: 0.4243676 test: 0.4282950 best: 0.4282950 (427) total: 2m 29s remaining: 3m 19s
428: learn: 0.4243473 test: 0.4282811 best: 0.4282811 (428) total: 2m 29s remaining: 3m 19s
429: learn: 0.4243329 test: 0.4282765 best: 0.4282765 (429) total: 2m 29s remaining: 3m 18s
430: learn: 0.4243032 test: 0.4282550 best: 0.4282550 (430) total: 2m 30s remaining: 3m 18s
431: learn: 0.4242694 test: 0.4282298 best: 0.4282298 (431) total: 2m 30s remaining: 3m 18s
432: learn: 0.4242107 test: 0.4281898 best: 0.4281898 (432) total: 2m 31s remaining: 3m 17s
433: learn: 0.4241849 test: 0.4281765 best: 0.4281765 (433) total: 2m 31s remaining: 3m 17s
434: learn: 0.4241271 test: 0.4281518 best: 0.4281518 (434) total: 2m 31s remaining: 3m 17s
435: learn: 0.4240835 test: 0.4281347 best: 0.4281347 (435) total: 2m 32s remaining: 3m 17s
436: learn: 0.4240535 test: 0.4281105 best: 0.4281105 (436) total: 2m 32s remaining: 3m 16s
437: learn: 0.4240027 test: 0.4280863 best: 0.4280863 (437) total: 2m 33s remaining: 3m 16s
438: learn: 0.4239854 test: 0.4280731 best: 0.4280731 (438) total: 2m 33s remaining: 3m 16s
439: learn: 0.4239391 test: 0.4280458 best: 0.4280458 (439) total: 2m 33s remaining: 3m 15s
440: learn: 0.4239109 test: 0.4280294 best: 0.4280294 (440) total: 2m 34s remaining: 3m 15s
441: learn: 0.4238921 test: 0.4280146 best: 0.4280146 (441) total: 2m 34s remaining: 3m 15s
442: learn: 0.4238450 test: 0.4279975 best: 0.4279975 (442) total: 2m 34s remaining: 3m 14s
443: learn: 0.4238357 test: 0.4279890 best: 0.4279890 (443) total: 2m 35s remaining: 3m 14s
444: learn: 0.4238161 test: 0.4279676 best: 0.4279676 (444) total: 2m 35s remaining: 3m 13s
445: learn: 0.4237623 test: 0.4279293 best: 0.4279293 (445) total: 2m 35s remaining: 3m 13s
446: learn: 0.4237300 test: 0.4279032 best: 0.4279032 (446) total: 2m 36s remaining: 3m 13s
447: learn: 0.4236567 test: 0.4278842 best: 0.4278842 (447) total: 2m 36s remaining: 3m 13s
448: learn: 0.4236191 test: 0.4278659 best: 0.4278659 (448) total: 2m 36s remaining: 3m 12s
449: learn: 0.4235899 test: 0.4278370 best: 0.4278370 (449) total: 2m 37s remaining: 3m 12s
450: learn: 0.4235778 test: 0.4278225 best: 0.4278225 (450) total: 2m 37s remaining: 3m 11s
451: learn: 0.4235725 test: 0.4278163 best: 0.4278163 (451) total: 2m 37s remaining: 3m 11s
452: learn: 0.4235277 test: 0.4277911 best: 0.4277911 (452) total: 2m 38s remaining: 3m 11s
453: learn: 0.4234797 test: 0.4277717 best: 0.4277717 (453) total: 2m 38s remaining: 3m 10s
454: learn: 0.4234685 test: 0.4277636 best: 0.4277636 (454) total: 2m 38s remaining: 3m 10s
455: learn: 0.4234537 test: 0.4277491 best: 0.4277491 (455) total: 2m 39s remaining: 3m 9s
456: learn: 0.4234390 test: 0.4277408 best: 0.4277408 (456) total: 2m 39s remaining: 3m 9s
457: learn: 0.4234302 test: 0.4277330 best: 0.4277330 (457) total: 2m 39s remaining: 3m 8s
458: learn: 0.4234044 test: 0.4277142 best: 0.4277142 (458) total: 2m 39s remaining: 3m 8s
459: learn: 0.4233610 test: 0.4276772 best: 0.4276772 (459) total: 2m 40s remaining: 3m 8s
460: learn: 0.4233086 test: 0.4276413 best: 0.4276413 (460) total: 2m 40s remaining: 3m 7s
461: learn: 0.4233076 test: 0.4276403 best: 0.4276403 (461) total: 2m 40s remaining: 3m 7s
462: learn: 0.4232989 test: 0.4276283 best: 0.4276283 (462) total: 2m 40s remaining: 3m 6s
463: learn: 0.4232537 test: 0.4275984 best: 0.4275984 (463) total: 2m 41s remaining: 3m 6s
464: learn: 0.4232400 test: 0.4275900 best: 0.4275900 (464) total: 2m 41s remaining: 3m 5s
465: learn: 0.4231939 test: 0.4275572 best: 0.4275572 (465) total: 2m 41s remaining: 3m 5s
466: learn: 0.4231491 test: 0.4275279 best: 0.4275279 (466) total: 2m 42s remaining: 3m 5s
467: learn: 0.4231343 test: 0.4275160 best: 0.4275160 (467) total: 2m 42s remaining: 3m 4s
468: learn: 0.4231217 test: 0.4275076 best: 0.4275076 (468) total: 2m 42s remaining: 3m 4s
469: learn: 0.4231012 test: 0.4274949 best: 0.4274949 (469) total: 2m 42s remaining: 3m 3s
470: learn: 0.4230672 test: 0.4274753 best: 0.4274753 (470) total: 2m 43s remaining: 3m 3s
471: learn: 0.4230219 test: 0.4274668 best: 0.4274668 (471) total: 2m 43s remaining: 3m 3s
472: learn: 0.4229895 test: 0.4274417 best: 0.4274417 (472) total: 2m 44s remaining: 3m 2s
473: learn: 0.4229617 test: 0.4274192 best: 0.4274192 (473) total: 2m 44s remaining: 3m 2s
474: learn: 0.4229458 test: 0.4274031 best: 0.4274031 (474) total: 2m 44s remaining: 3m 2s
475: learn: 0.4228826 test: 0.4273723 best: 0.4273723 (475) total: 2m 45s remaining: 3m 1s
476: learn: 0.4228503 test: 0.4273510 best: 0.4273510 (476) total: 2m 45s remaining: 3m 1s
477: learn: 0.4228032 test: 0.4273101 best: 0.4273101 (477) total: 2m 46s remaining: 3m 1s
478: learn: 0.4227637 test: 0.4272918 best: 0.4272918 (478) total: 2m 46s remaining: 3m 1s
479: learn: 0.4227210 test: 0.4272735 best: 0.4272735 (479) total: 2m 47s remaining: 3m
480: learn: 0.4227137 test: 0.4272693 best: 0.4272693 (480) total: 2m 47s remaining: 3m
481: learn: 0.4226770 test: 0.4272413 best: 0.4272413 (481) total: 2m 47s remaining: 3m
482: learn: 0.4226245 test: 0.4272106 best: 0.4272106 (482) total: 2m 48s remaining: 3m
483: learn: 0.4225792 test: 0.4271810 best: 0.4271810 (483) total: 2m 48s remaining: 2m 59s
484: learn: 0.4225336 test: 0.4271599 best: 0.4271599 (484) total: 2m 49s remaining: 2m 59s
485: learn: 0.4224746 test: 0.4271299 best: 0.4271299 (485) total: 2m 49s remaining: 2m 59s
486: learn: 0.4224411 test: 0.4271104 best: 0.4271104 (486) total: 2m 50s remaining: 2m 59s
487: learn: 0.4224288 test: 0.4271031 best: 0.4271031 (487) total: 2m 50s remaining: 2m 58s
488: learn: 0.4223834 test: 0.4270817 best: 0.4270817 (488) total: 2m 50s remaining: 2m 58s
489: learn: 0.4223632 test: 0.4270660 best: 0.4270660 (489) total: 2m 51s remaining: 2m 58s
490: learn: 0.4223211 test: 0.4270593 best: 0.4270593 (490) total: 2m 51s remaining: 2m 58s
491: learn: 0.4223044 test: 0.4270444 best: 0.4270444 (491) total: 2m 51s remaining: 2m 57s
492: learn: 0.4222639 test: 0.4270286 best: 0.4270286 (492) total: 2m 52s remaining: 2m 57s
493: learn: 0.4222418 test: 0.4270185 best: 0.4270185 (493) total: 2m 52s remaining: 2m 57s
494: learn: 0.4222153 test: 0.4270006 best: 0.4270006 (494) total: 2m 53s remaining: 2m 56s
495: learn: 0.4221897 test: 0.4269810 best: 0.4269810 (495) total: 2m 53s remaining: 2m 56s
496: learn: 0.4221230 test: 0.4269635 best: 0.4269635 (496) total: 2m 54s remaining: 2m 56s
497: learn: 0.4220754 test: 0.4269399 best: 0.4269399 (497) total: 2m 54s remaining: 2m 56s
498: learn: 0.4220341 test: 0.4269159 best: 0.4269159 (498) total: 2m 55s remaining: 2m 56s
499: learn: 0.4220244 test: 0.4269104 best: 0.4269104 (499) total: 2m 55s remaining: 2m 55s
500: learn: 0.4219699 test: 0.4268842 best: 0.4268842 (500) total: 2m 55s remaining: 2m 55s
501: learn: 0.4219315 test: 0.4268555 best: 0.4268555 (501) total: 2m 56s remaining: 2m 54s
502: learn: 0.4219074 test: 0.4268367 best: 0.4268367 (502) total: 2m 56s remaining: 2m 54s
503: learn: 0.4218460 test: 0.4268125 best: 0.4268125 (503) total: 2m 56s remaining: 2m 54s
504: learn: 0.4218344 test: 0.4268040 best: 0.4268040 (504) total: 2m 57s remaining: 2m 53s
505: learn: 0.4217831 test: 0.4267805 best: 0.4267805 (505) total: 2m 57s remaining: 2m 53s
506: learn: 0.4217342 test: 0.4267430 best: 0.4267430 (506) total: 2m 58s remaining: 2m 53s
507: learn: 0.4217132 test: 0.4267298 best: 0.4267298 (507) total: 2m 58s remaining: 2m 52s
508: learn: 0.4216844 test: 0.4267132 best: 0.4267132 (508) total: 2m 58s remaining: 2m 52s
509: learn: 0.4216622 test: 0.4266995 best: 0.4266995 (509) total: 2m 59s remaining: 2m 52s
510: learn: 0.4216340 test: 0.4266820 best: 0.4266820 (510) total: 2m 59s remaining: 2m 52s
511: learn: 0.4216292 test: 0.4266739 best: 0.4266739 (511) total: 3m remaining: 2m 51s
512: learn: 0.4215684 test: 0.4266381 best: 0.4266381 (512) total: 3m remaining: 2m 51s
513: learn: 0.4215217 test: 0.4265981 best: 0.4265981 (513) total: 3m remaining: 2m 51s
514: learn: 0.4215039 test: 0.4265835 best: 0.4265835 (514) total: 3m 1s remaining: 2m 50s
515: learn: 0.4214880 test: 0.4265738 best: 0.4265738 (515) total: 3m 1s remaining: 2m 50s
516: learn: 0.4214616 test: 0.4265531 best: 0.4265531 (516) total: 3m 1s remaining: 2m 49s
517: learn: 0.4214320 test: 0.4265511 best: 0.4265511 (517) total: 3m 2s remaining: 2m 49s
518: learn: 0.4213897 test: 0.4265318 best: 0.4265318 (518) total: 3m 2s remaining: 2m 49s
519: learn: 0.4213377 test: 0.4265026 best: 0.4265026 (519) total: 3m 3s remaining: 2m 49s
520: learn: 0.4212965 test: 0.4264921 best: 0.4264921 (520) total: 3m 3s remaining: 2m 48s
521: learn: 0.4212734 test: 0.4264826 best: 0.4264826 (521) total: 3m 4s remaining: 2m 48s
522: learn: 0.4212306 test: 0.4264581 best: 0.4264581 (522) total: 3m 4s remaining: 2m 48s
523: learn: 0.4211986 test: 0.4264297 best: 0.4264297 (523) total: 3m 5s remaining: 2m 48s
524: learn: 0.4211550 test: 0.4264182 best: 0.4264182 (524) total: 3m 5s remaining: 2m 47s
525: learn: 0.4211472 test: 0.4264069 best: 0.4264069 (525) total: 3m 5s remaining: 2m 47s
526: learn: 0.4211304 test: 0.4263924 best: 0.4263924 (526) total: 3m 6s remaining: 2m 47s
527: learn: 0.4210804 test: 0.4263687 best: 0.4263687 (527) total: 3m 6s remaining: 2m 46s
528: learn: 0.4210187 test: 0.4263308 best: 0.4263308 (528) total: 3m 6s remaining: 2m 46s
529: learn: 0.4209945 test: 0.4263138 best: 0.4263138 (529) total: 3m 7s remaining: 2m 46s
530: learn: 0.4209537 test: 0.4262768 best: 0.4262768 (530) total: 3m 7s remaining: 2m 46s
531: learn: 0.4209336 test: 0.4262608 best: 0.4262608 (531) total: 3m 8s remaining: 2m 45s
532: learn: 0.4209183 test: 0.4262488 best: 0.4262488 (532) total: 3m 8s remaining: 2m 45s
533: learn: 0.4208882 test: 0.4262297 best: 0.4262297 (533) total: 3m 9s remaining: 2m 45s
534: learn: 0.4208814 test: 0.4262224 best: 0.4262224 (534) total: 3m 9s remaining: 2m 44s
535: learn: 0.4208370 test: 0.4261943 best: 0.4261943 (535) total: 3m 9s remaining: 2m 44s
536: learn: 0.4208340 test: 0.4261921 best: 0.4261921 (536) total: 3m 10s remaining: 2m 43s
537: learn: 0.4208087 test: 0.4261722 best: 0.4261722 (537) total: 3m 10s remaining: 2m 43s
538: learn: 0.4207979 test: 0.4261621 best: 0.4261621 (538) total: 3m 10s remaining: 2m 43s
539: learn: 0.4207734 test: 0.4261524 best: 0.4261524 (539) total: 3m 11s remaining: 2m 42s
540: learn: 0.4207688 test: 0.4261465 best: 0.4261465 (540) total: 3m 11s remaining: 2m 42s
541: learn: 0.4207527 test: 0.4261427 best: 0.4261427 (541) total: 3m 11s remaining: 2m 41s
542: learn: 0.4207088 test: 0.4261295 best: 0.4261295 (542) total: 3m 11s remaining: 2m 41s
543: learn: 0.4206846 test: 0.4261169 best: 0.4261169 (543) total: 3m 12s remaining: 2m 41s
544: learn: 0.4206802 test: 0.4261109 best: 0.4261109 (544) total: 3m 12s remaining: 2m 40s
545: learn: 0.4206140 test: 0.4260765 best: 0.4260765 (545) total: 3m 13s remaining: 2m 40s
546: learn: 0.4205793 test: 0.4260557 best: 0.4260557 (546) total: 3m 13s remaining: 2m 40s
547: learn: 0.4205399 test: 0.4260423 best: 0.4260423 (547) total: 3m 13s remaining: 2m 39s
548: learn: 0.4205275 test: 0.4260348 best: 0.4260348 (548) total: 3m 14s remaining: 2m 39s
549: learn: 0.4205249 test: 0.4260336 best: 0.4260336 (549) total: 3m 14s remaining: 2m 38s
550: learn: 0.4204244 test: 0.4260183 best: 0.4260183 (550) total: 3m 14s remaining: 2m 38s
551: learn: 0.4203990 test: 0.4260036 best: 0.4260036 (551) total: 3m 15s remaining: 2m 38s
552: learn: 0.4203604 test: 0.4259822 best: 0.4259822 (552) total: 3m 15s remaining: 2m 38s
553: learn: 0.4203508 test: 0.4259705 best: 0.4259705 (553) total: 3m 15s remaining: 2m 37s
554: learn: 0.4203311 test: 0.4259620 best: 0.4259620 (554) total: 3m 16s remaining: 2m 37s
555: learn: 0.4202606 test: 0.4259082 best: 0.4259082 (555) total: 3m 16s remaining: 2m 36s
556: learn: 0.4202447 test: 0.4258965 best: 0.4258965 (556) total: 3m 16s remaining: 2m 36s
557: learn: 0.4202299 test: 0.4258807 best: 0.4258807 (557) total: 3m 17s remaining: 2m 36s
558: learn: 0.4202052 test: 0.4258662 best: 0.4258662 (558) total: 3m 17s remaining: 2m 35s
559: learn: 0.4201979 test: 0.4258560 best: 0.4258560 (559) total: 3m 17s remaining: 2m 35s
560: learn: 0.4201820 test: 0.4258402 best: 0.4258402 (560) total: 3m 18s remaining: 2m 35s
561: learn: 0.4201482 test: 0.4258260 best: 0.4258260 (561) total: 3m 18s remaining: 2m 34s
562: learn: 0.4201197 test: 0.4258074 best: 0.4258074 (562) total: 3m 19s remaining: 2m 34s
563: learn: 0.4200994 test: 0.4257940 best: 0.4257940 (563) total: 3m 19s remaining: 2m 34s
564: learn: 0.4200727 test: 0.4257816 best: 0.4257816 (564) total: 3m 20s remaining: 2m 34s
565: learn: 0.4200609 test: 0.4257700 best: 0.4257700 (565) total: 3m 20s remaining: 2m 33s
566: learn: 0.4200354 test: 0.4257483 best: 0.4257483 (566) total: 3m 20s remaining: 2m 33s
567: learn: 0.4200156 test: 0.4257341 best: 0.4257341 (567) total: 3m 21s remaining: 2m 32s
568: learn: 0.4199921 test: 0.4257155 best: 0.4257155 (568) total: 3m 21s remaining: 2m 32s
569: learn: 0.4199465 test: 0.4256801 best: 0.4256801 (569) total: 3m 21s remaining: 2m 32s
570: learn: 0.4198987 test: 0.4256626 best: 0.4256626 (570) total: 3m 22s remaining: 2m 31s
571: learn: 0.4198381 test: 0.4256322 best: 0.4256322 (571) total: 3m 22s remaining: 2m 31s
572: learn: 0.4198134 test: 0.4256043 best: 0.4256043 (572) total: 3m 23s remaining: 2m 31s
573: learn: 0.4197813 test: 0.4255922 best: 0.4255922 (573) total: 3m 23s remaining: 2m 31s
574: learn: 0.4197359 test: 0.4255740 best: 0.4255740 (574) total: 3m 24s remaining: 2m 30s
575: learn: 0.4196999 test: 0.4255558 best: 0.4255558 (575) total: 3m 24s remaining: 2m 30s
576: learn: 0.4196625 test: 0.4255404 best: 0.4255404 (576) total: 3m 25s remaining: 2m 30s
577: learn: 0.4195979 test: 0.4255275 best: 0.4255275 (577) total: 3m 25s remaining: 2m 30s
578: learn: 0.4195738 test: 0.4255145 best: 0.4255145 (578) total: 3m 26s remaining: 2m 29s
579: learn: 0.4195428 test: 0.4255048 best: 0.4255048 (579) total: 3m 26s remaining: 2m 29s
580: learn: 0.4195317 test: 0.4254952 best: 0.4254952 (580) total: 3m 26s remaining: 2m 29s
581: learn: 0.4195221 test: 0.4254866 best: 0.4254866 (581) total: 3m 27s remaining: 2m 28s
582: learn: 0.4194977 test: 0.4254732 best: 0.4254732 (582) total: 3m 27s remaining: 2m 28s
583: learn: 0.4194419 test: 0.4254273 best: 0.4254273 (583) total: 3m 28s remaining: 2m 28s
584: learn: 0.4194070 test: 0.4254060 best: 0.4254060 (584) total: 3m 28s remaining: 2m 28s
585: learn: 0.4193735 test: 0.4253796 best: 0.4253796 (585) total: 3m 29s remaining: 2m 27s
586: learn: 0.4193374 test: 0.4253629 best: 0.4253629 (586) total: 3m 29s remaining: 2m 27s
587: learn: 0.4193262 test: 0.4253527 best: 0.4253527 (587) total: 3m 30s remaining: 2m 27s
588: learn: 0.4193116 test: 0.4253462 best: 0.4253462 (588) total: 3m 30s remaining: 2m 26s
589: learn: 0.4193068 test: 0.4253388 best: 0.4253388 (589) total: 3m 30s remaining: 2m 26s
590: learn: 0.4192582 test: 0.4253321 best: 0.4253321 (590) total: 3m 31s remaining: 2m 26s
591: learn: 0.4191921 test: 0.4252989 best: 0.4252989 (591) total: 3m 31s remaining: 2m 25s
592: learn: 0.4191740 test: 0.4252878 best: 0.4252878 (592) total: 3m 32s remaining: 2m 25s
593: learn: 0.4191593 test: 0.4252739 best: 0.4252739 (593) total: 3m 32s remaining: 2m 25s
594: learn: 0.4191483 test: 0.4252695 best: 0.4252695 (594) total: 3m 32s remaining: 2m 24s
595: learn: 0.4191301 test: 0.4252609 best: 0.4252609 (595) total: 3m 32s remaining: 2m 24s
596: learn: 0.4190960 test: 0.4252378 best: 0.4252378 (596) total: 3m 33s remaining: 2m 24s
597: learn: 0.4190485 test: 0.4252145 best: 0.4252145 (597) total: 3m 33s remaining: 2m 23s
598: learn: 0.4190204 test: 0.4251984 best: 0.4251984 (598) total: 3m 34s remaining: 2m 23s
599: learn: 0.4190188 test: 0.4251966 best: 0.4251966 (599) total: 3m 34s remaining: 2m 22s
600: learn: 0.4190154 test: 0.4251943 best: 0.4251943 (600) total: 3m 34s remaining: 2m 22s
601: learn: 0.4189940 test: 0.4251873 best: 0.4251873 (601) total: 3m 34s remaining: 2m 22s
602: learn: 0.4189384 test: 0.4251528 best: 0.4251528 (602) total: 3m 35s remaining: 2m 21s
603: learn: 0.4189283 test: 0.4251445 best: 0.4251445 (603) total: 3m 35s remaining: 2m 21s
604: learn: 0.4188927 test: 0.4251258 best: 0.4251258 (604) total: 3m 36s remaining: 2m 21s
605: learn: 0.4188646 test: 0.4251035 best: 0.4251035 (605) total: 3m 36s remaining: 2m 20s
606: learn: 0.4188155 test: 0.4250936 best: 0.4250936 (606) total: 3m 37s remaining: 2m 20s
607: learn: 0.4187696 test: 0.4250708 best: 0.4250708 (607) total: 3m 37s remaining: 2m 20s
608: learn: 0.4187432 test: 0.4250519 best: 0.4250519 (608) total: 3m 38s remaining: 2m 20s
609: learn: 0.4187216 test: 0.4250370 best: 0.4250370 (609) total: 3m 38s remaining: 2m 19s
610: learn: 0.4186926 test: 0.4250182 best: 0.4250182 (610) total: 3m 39s remaining: 2m 19s
611: learn: 0.4186554 test: 0.4249879 best: 0.4249879 (611) total: 3m 39s remaining: 2m 19s
612: learn: 0.4186319 test: 0.4249766 best: 0.4249766 (612) total: 3m 39s remaining: 2m 18s
613: learn: 0.4186227 test: 0.4249709 best: 0.4249709 (613) total: 3m 40s remaining: 2m 18s
614: learn: 0.4186022 test: 0.4249629 best: 0.4249629 (614) total: 3m 40s remaining: 2m 18s
615: learn: 0.4185443 test: 0.4249405 best: 0.4249405 (615) total: 3m 41s remaining: 2m 17s
616: learn: 0.4185183 test: 0.4249225 best: 0.4249225 (616) total: 3m 41s remaining: 2m 17s
617: learn: 0.4184890 test: 0.4248999 best: 0.4248999 (617) total: 3m 42s remaining: 2m 17s
618: learn: 0.4184504 test: 0.4248874 best: 0.4248874 (618) total: 3m 42s remaining: 2m 16s
619: learn: 0.4184438 test: 0.4248814 best: 0.4248814 (619) total: 3m 42s remaining: 2m 16s
620: learn: 0.4184243 test: 0.4248721 best: 0.4248721 (620) total: 3m 43s remaining: 2m 16s
621: learn: 0.4183971 test: 0.4248647 best: 0.4248647 (621) total: 3m 43s remaining: 2m 15s
622: learn: 0.4183601 test: 0.4248487 best: 0.4248487 (622) total: 3m 44s remaining: 2m 15s
623: learn: 0.4183396 test: 0.4248393 best: 0.4248393 (623) total: 3m 44s remaining: 2m 15s
624: learn: 0.4182883 test: 0.4248265 best: 0.4248265 (624) total: 3m 44s remaining: 2m 14s
625: learn: 0.4182729 test: 0.4248203 best: 0.4248203 (625) total: 3m 45s remaining: 2m 14s
626: learn: 0.4182404 test: 0.4248112 best: 0.4248112 (626) total: 3m 45s remaining: 2m 14s
627: learn: 0.4182254 test: 0.4247957 best: 0.4247957 (627) total: 3m 45s remaining: 2m 13s
628: learn: 0.4182016 test: 0.4247862 best: 0.4247862 (628) total: 3m 46s remaining: 2m 13s
629: learn: 0.4181726 test: 0.4247668 best: 0.4247668 (629) total: 3m 46s remaining: 2m 13s
630: learn: 0.4181690 test: 0.4247664 best: 0.4247664 (630) total: 3m 47s remaining: 2m 12s
631: learn: 0.4181646 test: 0.4247652 best: 0.4247652 (631) total: 3m 47s remaining: 2m 12s
632: learn: 0.4181408 test: 0.4247561 best: 0.4247561 (632) total: 3m 47s remaining: 2m 11s
633: learn: 0.4181076 test: 0.4247368 best: 0.4247368 (633) total: 3m 48s remaining: 2m 11s
634: learn: 0.4180851 test: 0.4247237 best: 0.4247237 (634) total: 3m 48s remaining: 2m 11s
635: learn: 0.4180641 test: 0.4247058 best: 0.4247058 (635) total: 3m 49s remaining: 2m 11s
636: learn: 0.4180245 test: 0.4246859 best: 0.4246859 (636) total: 3m 49s remaining: 2m 10s
637: learn: 0.4180223 test: 0.4246837 best: 0.4246837 (637) total: 3m 49s remaining: 2m 10s
638: learn: 0.4179902 test: 0.4246718 best: 0.4246718 (638) total: 3m 50s remaining: 2m 10s
639: learn: 0.4179532 test: 0.4246548 best: 0.4246548 (639) total: 3m 50s remaining: 2m 9s
640: learn: 0.4179375 test: 0.4246485 best: 0.4246485 (640) total: 3m 51s remaining: 2m 9s
641: learn: 0.4178976 test: 0.4246352 best: 0.4246352 (641) total: 3m 51s remaining: 2m 9s
642: learn: 0.4178602 test: 0.4246045 best: 0.4246045 (642) total: 3m 51s remaining: 2m 8s
643: learn: 0.4178452 test: 0.4245955 best: 0.4245955 (643) total: 3m 52s remaining: 2m 8s
644: learn: 0.4178391 test: 0.4245912 best: 0.4245912 (644) total: 3m 52s remaining: 2m 8s
645: learn: 0.4178033 test: 0.4245694 best: 0.4245694 (645) total: 3m 53s remaining: 2m 7s
646: learn: 0.4177770 test: 0.4245543 best: 0.4245543 (646) total: 3m 53s remaining: 2m 7s
647: learn: 0.4177255 test: 0.4245309 best: 0.4245309 (647) total: 3m 54s remaining: 2m 7s
648: learn: 0.4176953 test: 0.4245147 best: 0.4245147 (648) total: 3m 54s remaining: 2m 6s
649: learn: 0.4176859 test: 0.4245066 best: 0.4245066 (649) total: 3m 54s remaining: 2m 6s
650: learn: 0.4176557 test: 0.4244985 best: 0.4244985 (650) total: 3m 55s remaining: 2m 6s
651: learn: 0.4176338 test: 0.4244796 best: 0.4244796 (651) total: 3m 55s remaining: 2m 5s
652: learn: 0.4176282 test: 0.4244760 best: 0.4244760 (652) total: 3m 56s remaining: 2m 5s
653: learn: 0.4176261 test: 0.4244740 best: 0.4244740 (653) total: 3m 56s remaining: 2m 5s
654: learn: 0.4175513 test: 0.4244597 best: 0.4244597 (654) total: 3m 56s remaining: 2m 4s
655: learn: 0.4175430 test: 0.4244607 best: 0.4244597 (654) total: 3m 57s remaining: 2m 4s
656: learn: 0.4175193 test: 0.4244496 best: 0.4244496 (656) total: 3m 57s remaining: 2m 3s
657: learn: 0.4175031 test: 0.4244378 best: 0.4244378 (657) total: 3m 57s remaining: 2m 3s
658: learn: 0.4174750 test: 0.4244284 best: 0.4244284 (658) total: 3m 58s remaining: 2m 3s
659: learn: 0.4174664 test: 0.4244256 best: 0.4244256 (659) total: 3m 58s remaining: 2m 2s
660: learn: 0.4174527 test: 0.4244141 best: 0.4244141 (660) total: 3m 58s remaining: 2m 2s
661: learn: 0.4174050 test: 0.4243955 best: 0.4243955 (661) total: 3m 59s remaining: 2m 2s
662: learn: 0.4173996 test: 0.4243944 best: 0.4243944 (662) total: 3m 59s remaining: 2m 1s
663: learn: 0.4173720 test: 0.4243666 best: 0.4243666 (663) total: 3m 59s remaining: 2m 1s
664: learn: 0.4173301 test: 0.4243601 best: 0.4243601 (664) total: 4m remaining: 2m 1s
665: learn: 0.4172889 test: 0.4243440 best: 0.4243440 (665) total: 4m 1s remaining: 2m
666: learn: 0.4172448 test: 0.4243370 best: 0.4243370 (666) total: 4m 1s remaining: 2m
667: learn: 0.4172260 test: 0.4243194 best: 0.4243194 (667) total: 4m 2s remaining: 2m
668: learn: 0.4172006 test: 0.4242982 best: 0.4242982 (668) total: 4m 2s remaining: 2m
669: learn: 0.4171515 test: 0.4242902 best: 0.4242902 (669) total: 4m 3s remaining: 1m 59s
670: learn: 0.4171318 test: 0.4242611 best: 0.4242611 (670) total: 4m 3s remaining: 1m 59s
671: learn: 0.4171052 test: 0.4242418 best: 0.4242418 (671) total: 4m 4s remaining: 1m 59s
672: learn: 0.4170615 test: 0.4242137 best: 0.4242137 (672) total: 4m 4s remaining: 1m 58s
673: learn: 0.4170371 test: 0.4242051 best: 0.4242051 (673) total: 4m 4s remaining: 1m 58s
674: learn: 0.4170323 test: 0.4241983 best: 0.4241983 (674) total: 4m 5s remaining: 1m 58s
675: learn: 0.4170295 test: 0.4241958 best: 0.4241958 (675) total: 4m 5s remaining: 1m 57s
676: learn: 0.4170013 test: 0.4241750 best: 0.4241750 (676) total: 4m 5s remaining: 1m 57s
677: learn: 0.4169975 test: 0.4241691 best: 0.4241691 (677) total: 4m 5s remaining: 1m 56s
678: learn: 0.4169661 test: 0.4241468 best: 0.4241468 (678) total: 4m 6s remaining: 1m 56s
679: learn: 0.4169344 test: 0.4241381 best: 0.4241381 (679) total: 4m 6s remaining: 1m 56s
680: learn: 0.4168908 test: 0.4241086 best: 0.4241086 (680) total: 4m 7s remaining: 1m 55s
681: learn: 0.4168488 test: 0.4241068 best: 0.4241068 (681) total: 4m 7s remaining: 1m 55s
682: learn: 0.4168309 test: 0.4240961 best: 0.4240961 (682) total: 4m 8s remaining: 1m 55s
683: learn: 0.4167870 test: 0.4240861 best: 0.4240861 (683) total: 4m 8s remaining: 1m 54s
684: learn: 0.4167458 test: 0.4240724 best: 0.4240724 (684) total: 4m 9s remaining: 1m 54s
685: learn: 0.4167358 test: 0.4240646 best: 0.4240646 (685) total: 4m 9s remaining: 1m 54s
686: learn: 0.4167316 test: 0.4240607 best: 0.4240607 (686) total: 4m 9s remaining: 1m 53s
687: learn: 0.4166487 test: 0.4240216 best: 0.4240216 (687) total: 4m 10s remaining: 1m 53s
688: learn: 0.4166364 test: 0.4240163 best: 0.4240163 (688) total: 4m 10s remaining: 1m 53s
689: learn: 0.4165585 test: 0.4240033 best: 0.4240033 (689) total: 4m 11s remaining: 1m 52s
690: learn: 0.4165559 test: 0.4240024 best: 0.4240024 (690) total: 4m 11s remaining: 1m 52s
691: learn: 0.4165396 test: 0.4239871 best: 0.4239871 (691) total: 4m 11s remaining: 1m 51s
692: learn: 0.4165182 test: 0.4239760 best: 0.4239760 (692) total: 4m 11s remaining: 1m 51s
693: learn: 0.4164684 test: 0.4239623 best: 0.4239623 (693) total: 4m 12s remaining: 1m 51s
694: learn: 0.4164506 test: 0.4239546 best: 0.4239546 (694) total: 4m 12s remaining: 1m 51s
695: learn: 0.4164278 test: 0.4239469 best: 0.4239469 (695) total: 4m 13s remaining: 1m 50s
696: learn: 0.4163895 test: 0.4239242 best: 0.4239242 (696) total: 4m 13s remaining: 1m 50s
697: learn: 0.4163726 test: 0.4239192 best: 0.4239192 (697) total: 4m 14s remaining: 1m 50s
698: learn: 0.4163667 test: 0.4239140 best: 0.4239140 (698) total: 4m 14s remaining: 1m 49s
699: learn: 0.4163667 test: 0.4239140 best: 0.4239140 (699) total: 4m 14s remaining: 1m 49s
700: learn: 0.4163548 test: 0.4239039 best: 0.4239039 (700) total: 4m 15s remaining: 1m 48s
701: learn: 0.4163176 test: 0.4238942 best: 0.4238942 (701) total: 4m 15s remaining: 1m 48s
702: learn: 0.4162147 test: 0.4238419 best: 0.4238419 (702) total: 4m 16s remaining: 1m 48s
703: learn: 0.4161894 test: 0.4238298 best: 0.4238298 (703) total: 4m 16s remaining: 1m 47s
704: learn: 0.4161761 test: 0.4238185 best: 0.4238185 (704) total: 4m 16s remaining: 1m 47s
705: learn: 0.4161473 test: 0.4238146 best: 0.4238146 (705) total: 4m 17s remaining: 1m 47s
706: learn: 0.4160964 test: 0.4237953 best: 0.4237953 (706) total: 4m 18s remaining: 1m 47s
707: learn: 0.4160835 test: 0.4237888 best: 0.4237888 (707) total: 4m 18s remaining: 1m 46s
708: learn: 0.4160753 test: 0.4237797 best: 0.4237797 (708) total: 4m 19s remaining: 1m 46s
709: learn: 0.4160634 test: 0.4237710 best: 0.4237710 (709) total: 4m 19s remaining: 1m 45s
710: learn: 0.4160487 test: 0.4237686 best: 0.4237686 (710) total: 4m 19s remaining: 1m 45s
711: learn: 0.4159909 test: 0.4237337 best: 0.4237337 (711) total: 4m 20s remaining: 1m 45s
712: learn: 0.4159427 test: 0.4237178 best: 0.4237178 (712) total: 4m 20s remaining: 1m 45s
713: learn: 0.4159183 test: 0.4237068 best: 0.4237068 (713) total: 4m 21s remaining: 1m 44s
714: learn: 0.4159148 test: 0.4237042 best: 0.4237042 (714) total: 4m 21s remaining: 1m 44s
715: learn: 0.4158882 test: 0.4236852 best: 0.4236852 (715) total: 4m 22s remaining: 1m 44s
716: learn: 0.4158525 test: 0.4236791 best: 0.4236791 (716) total: 4m 22s remaining: 1m 43s
717: learn: 0.4158288 test: 0.4236593 best: 0.4236593 (717) total: 4m 23s remaining: 1m 43s
718: learn: 0.4157804 test: 0.4236064 best: 0.4236064 (718) total: 4m 23s remaining: 1m 42s
719: learn: 0.4157480 test: 0.4235860 best: 0.4235860 (719) total: 4m 24s remaining: 1m 42s
720: learn: 0.4157407 test: 0.4235814 best: 0.4235814 (720) total: 4m 24s remaining: 1m 42s
721: learn: 0.4157286 test: 0.4235730 best: 0.4235730 (721) total: 4m 24s remaining: 1m 41s
722: learn: 0.4156898 test: 0.4235523 best: 0.4235523 (722) total: 4m 25s remaining: 1m 41s
723: learn: 0.4156398 test: 0.4235342 best: 0.4235342 (723) total: 4m 25s remaining: 1m 41s
724: learn: 0.4155934 test: 0.4235141 best: 0.4235141 (724) total: 4m 26s remaining: 1m 40s
725: learn: 0.4155648 test: 0.4234930 best: 0.4234930 (725) total: 4m 26s remaining: 1m 40s
726: learn: 0.4155401 test: 0.4234751 best: 0.4234751 (726) total: 4m 27s remaining: 1m 40s
727: learn: 0.4155202 test: 0.4234624 best: 0.4234624 (727) total: 4m 27s remaining: 1m 39s
728: learn: 0.4154971 test: 0.4234494 best: 0.4234494 (728) total: 4m 28s remaining: 1m 39s
729: learn: 0.4154958 test: 0.4234464 best: 0.4234464 (729) total: 4m 28s remaining: 1m 39s
730: learn: 0.4154952 test: 0.4234461 best: 0.4234461 (730) total: 4m 28s remaining: 1m 38s
731: learn: 0.4154743 test: 0.4234433 best: 0.4234433 (731) total: 4m 28s remaining: 1m 38s
732: learn: 0.4154681 test: 0.4234378 best: 0.4234378 (732) total: 4m 29s remaining: 1m 38s
733: learn: 0.4154551 test: 0.4234288 best: 0.4234288 (733) total: 4m 29s remaining: 1m 37s
734: learn: 0.4154429 test: 0.4234176 best: 0.4234176 (734) total: 4m 29s remaining: 1m 37s
735: learn: 0.4154225 test: 0.4234100 best: 0.4234100 (735) total: 4m 30s remaining: 1m 36s
736: learn: 0.4154057 test: 0.4234013 best: 0.4234013 (736) total: 4m 30s remaining: 1m 36s
737: learn: 0.4153886 test: 0.4233911 best: 0.4233911 (737) total: 4m 31s remaining: 1m 36s
738: learn: 0.4153830 test: 0.4233865 best: 0.4233865 (738) total: 4m 31s remaining: 1m 35s
739: learn: 0.4153553 test: 0.4233643 best: 0.4233643 (739) total: 4m 32s remaining: 1m 35s
740: learn: 0.4153178 test: 0.4233436 best: 0.4233436 (740) total: 4m 32s remaining: 1m 35s
741: learn: 0.4152871 test: 0.4233185 best: 0.4233185 (741) total: 4m 33s remaining: 1m 34s
742: learn: 0.4152145 test: 0.4233082 best: 0.4233082 (742) total: 4m 33s remaining: 1m 34s
743: learn: 0.4151833 test: 0.4233003 best: 0.4233003 (743) total: 4m 34s remaining: 1m 34s
744: learn: 0.4151177 test: 0.4232854 best: 0.4232854 (744) total: 4m 34s remaining: 1m 33s
745: learn: 0.4151176 test: 0.4232851 best: 0.4232851 (745) total: 4m 34s remaining: 1m 33s
746: learn: 0.4151071 test: 0.4232814 best: 0.4232814 (746) total: 4m 35s remaining: 1m 33s
747: learn: 0.4150835 test: 0.4232662 best: 0.4232662 (747) total: 4m 35s remaining: 1m 32s
748: learn: 0.4150297 test: 0.4232420 best: 0.4232420 (748) total: 4m 36s remaining: 1m 32s
749: learn: 0.4149838 test: 0.4232225 best: 0.4232225 (749) total: 4m 36s remaining: 1m 32s
750: learn: 0.4149587 test: 0.4232065 best: 0.4232065 (750) total: 4m 37s remaining: 1m 31s
751: learn: 0.4149306 test: 0.4231836 best: 0.4231836 (751) total: 4m 37s remaining: 1m 31s
752: learn: 0.4149154 test: 0.4231734 best: 0.4231734 (752) total: 4m 38s remaining: 1m 31s
753: learn: 0.4148906 test: 0.4231601 best: 0.4231601 (753) total: 4m 38s remaining: 1m 30s
754: learn: 0.4148520 test: 0.4231442 best: 0.4231442 (754) total: 4m 39s remaining: 1m 30s
755: learn: 0.4148327 test: 0.4231401 best: 0.4231401 (755) total: 4m 39s remaining: 1m 30s
756: learn: 0.4148326 test: 0.4231398 best: 0.4231398 (756) total: 4m 39s remaining: 1m 29s
757: learn: 0.4147925 test: 0.4231225 best: 0.4231225 (757) total: 4m 40s remaining: 1m 29s
758: learn: 0.4147528 test: 0.4231045 best: 0.4231045 (758) total: 4m 40s remaining: 1m 29s
759: learn: 0.4147382 test: 0.4231004 best: 0.4231004 (759) total: 4m 40s remaining: 1m 28s
760: learn: 0.4147131 test: 0.4230768 best: 0.4230768 (760) total: 4m 41s remaining: 1m 28s
761: learn: 0.4146956 test: 0.4230695 best: 0.4230695 (761) total: 4m 41s remaining: 1m 27s
762: learn: 0.4146199 test: 0.4230342 best: 0.4230342 (762) total: 4m 41s remaining: 1m 27s
763: learn: 0.4145708 test: 0.4230175 best: 0.4230175 (763) total: 4m 42s remaining: 1m 27s
764: learn: 0.4145536 test: 0.4230110 best: 0.4230110 (764) total: 4m 42s remaining: 1m 26s
765: learn: 0.4145288 test: 0.4230019 best: 0.4230019 (765) total: 4m 43s remaining: 1m 26s
766: learn: 0.4145136 test: 0.4229872 best: 0.4229872 (766) total: 4m 43s remaining: 1m 26s
767: learn: 0.4145135 test: 0.4229870 best: 0.4229870 (767) total: 4m 43s remaining: 1m 25s
768: learn: 0.4144804 test: 0.4229856 best: 0.4229856 (768) total: 4m 44s remaining: 1m 25s
769: learn: 0.4144738 test: 0.4229767 best: 0.4229767 (769) total: 4m 44s remaining: 1m 24s
770: learn: 0.4144511 test: 0.4229655 best: 0.4229655 (770) total: 4m 44s remaining: 1m 24s
771: learn: 0.4144305 test: 0.4229609 best: 0.4229609 (771) total: 4m 45s remaining: 1m 24s
772: learn: 0.4144057 test: 0.4229373 best: 0.4229373 (772) total: 4m 45s remaining: 1m 23s
773: learn: 0.4144009 test: 0.4229330 best: 0.4229330 (773) total: 4m 45s remaining: 1m 23s
774: learn: 0.4143761 test: 0.4229135 best: 0.4229135 (774) total: 4m 46s remaining: 1m 23s
775: learn: 0.4143608 test: 0.4229017 best: 0.4229017 (775) total: 4m 46s remaining: 1m 22s
776: learn: 0.4143606 test: 0.4229017 best: 0.4229017 (776) total: 4m 46s remaining: 1m 22s
777: learn: 0.4143495 test: 0.4228903 best: 0.4228903 (777) total: 4m 47s remaining: 1m 21s
778: learn: 0.4142924 test: 0.4228613 best: 0.4228613 (778) total: 4m 47s remaining: 1m 21s
779: learn: 0.4142592 test: 0.4228444 best: 0.4228444 (779) total: 4m 48s remaining: 1m 21s
780: learn: 0.4142354 test: 0.4228200 best: 0.4228200 (780) total: 4m 48s remaining: 1m 20s
781: learn: 0.4142185 test: 0.4228127 best: 0.4228127 (781) total: 4m 49s remaining: 1m 20s
782: learn: 0.4141615 test: 0.4227951 best: 0.4227951 (782) total: 4m 49s remaining: 1m 20s
783: learn: 0.4141012 test: 0.4227947 best: 0.4227947 (783) total: 4m 50s remaining: 1m 19s
784: learn: 0.4140561 test: 0.4227836 best: 0.4227836 (784) total: 4m 50s remaining: 1m 19s
785: learn: 0.4140542 test: 0.4227825 best: 0.4227825 (785) total: 4m 51s remaining: 1m 19s
786: learn: 0.4140223 test: 0.4227575 best: 0.4227575 (786) total: 4m 51s remaining: 1m 18s
787: learn: 0.4139499 test: 0.4227279 best: 0.4227279 (787) total: 4m 52s remaining: 1m 18s
788: learn: 0.4139165 test: 0.4227125 best: 0.4227125 (788) total: 4m 52s remaining: 1m 18s
789: learn: 0.4138781 test: 0.4226989 best: 0.4226989 (789) total: 4m 53s remaining: 1m 17s
790: learn: 0.4138655 test: 0.4226871 best: 0.4226871 (790) total: 4m 53s remaining: 1m 17s
791: learn: 0.4138573 test: 0.4226835 best: 0.4226835 (791) total: 4m 53s remaining: 1m 17s
792: learn: 0.4138544 test: 0.4226818 best: 0.4226818 (792) total: 4m 53s remaining: 1m 16s
793: learn: 0.4138260 test: 0.4226594 best: 0.4226594 (793) total: 4m 53s remaining: 1m 16s
794: learn: 0.4138116 test: 0.4226571 best: 0.4226571 (794) total: 4m 54s remaining: 1m 15s
795: learn: 0.4138069 test: 0.4226525 best: 0.4226525 (795) total: 4m 54s remaining: 1m 15s
796: learn: 0.4138031 test: 0.4226487 best: 0.4226487 (796) total: 4m 54s remaining: 1m 15s
797: learn: 0.4137996 test: 0.4226477 best: 0.4226477 (797) total: 4m 54s remaining: 1m 14s
798: learn: 0.4137984 test: 0.4226467 best: 0.4226467 (798) total: 4m 54s remaining: 1m 14s
799: learn: 0.4137927 test: 0.4226424 best: 0.4226424 (799) total: 4m 55s remaining: 1m 13s
800: learn: 0.4137915 test: 0.4226411 best: 0.4226411 (800) total: 4m 55s remaining: 1m 13s
801: learn: 0.4137188 test: 0.4226284 best: 0.4226284 (801) total: 4m 55s remaining: 1m 12s
802: learn: 0.4136968 test: 0.4226073 best: 0.4226073 (802) total: 4m 56s remaining: 1m 12s
803: learn: 0.4136952 test: 0.4226061 best: 0.4226061 (803) total: 4m 56s remaining: 1m 12s
804: learn: 0.4136895 test: 0.4225986 best: 0.4225986 (804) total: 4m 56s remaining: 1m 11s
805: learn: 0.4136880 test: 0.4225979 best: 0.4225979 (805) total: 4m 56s remaining: 1m 11s
806: learn: 0.4136879 test: 0.4225977 best: 0.4225977 (806) total: 4m 56s remaining: 1m 10s
807: learn: 0.4136722 test: 0.4225909 best: 0.4225909 (807) total: 4m 57s remaining: 1m 10s
808: learn: 0.4136690 test: 0.4225893 best: 0.4225893 (808) total: 4m 57s remaining: 1m 10s
809: learn: 0.4136671 test: 0.4225878 best: 0.4225878 (809) total: 4m 57s remaining: 1m 9s
810: learn: 0.4136458 test: 0.4225879 best: 0.4225878 (809) total: 4m 58s remaining: 1m 9s
811: learn: 0.4136125 test: 0.4225617 best: 0.4225617 (811) total: 4m 58s remaining: 1m 9s
812: learn: 0.4135579 test: 0.4225374 best: 0.4225374 (812) total: 4m 59s remaining: 1m 8s
813: learn: 0.4135389 test: 0.4225262 best: 0.4225262 (813) total: 4m 59s remaining: 1m 8s
814: learn: 0.4135130 test: 0.4225163 best: 0.4225163 (814) total: 5m remaining: 1m 8s
815: learn: 0.4135064 test: 0.4225169 best: 0.4225163 (814) total: 5m remaining: 1m 7s
816: learn: 0.4134477 test: 0.4224812 best: 0.4224812 (816) total: 5m 1s remaining: 1m 7s
817: learn: 0.4134243 test: 0.4224660 best: 0.4224660 (817) total: 5m 1s remaining: 1m 7s
818: learn: 0.4134230 test: 0.4224648 best: 0.4224648 (818) total: 5m 1s remaining: 1m 6s
819: learn: 0.4134030 test: 0.4224561 best: 0.4224561 (819) total: 5m 2s remaining: 1m 6s
820: learn: 0.4133942 test: 0.4224473 best: 0.4224473 (820) total: 5m 2s remaining: 1m 5s
821: learn: 0.4133786 test: 0.4224463 best: 0.4224463 (821) total: 5m 2s remaining: 1m 5s
822: learn: 0.4133759 test: 0.4224454 best: 0.4224454 (822) total: 5m 3s remaining: 1m 5s
823: learn: 0.4133285 test: 0.4224340 best: 0.4224340 (823) total: 5m 3s remaining: 1m 4s
824: learn: 0.4133284 test: 0.4224339 best: 0.4224339 (824) total: 5m 3s remaining: 1m 4s
825: learn: 0.4132870 test: 0.4224159 best: 0.4224159 (825) total: 5m 4s remaining: 1m 4s
826: learn: 0.4132622 test: 0.4224037 best: 0.4224037 (826) total: 5m 4s remaining: 1m 3s
827: learn: 0.4132604 test: 0.4224021 best: 0.4224021 (827) total: 5m 4s remaining: 1m 3s
828: learn: 0.4132583 test: 0.4224004 best: 0.4224004 (828) total: 5m 4s remaining: 1m 2s
829: learn: 0.4131964 test: 0.4223602 best: 0.4223602 (829) total: 5m 5s remaining: 1m 2s
830: learn: 0.4131648 test: 0.4223529 best: 0.4223529 (830) total: 5m 6s remaining: 1m 2s
831: learn: 0.4131439 test: 0.4223489 best: 0.4223489 (831) total: 5m 6s remaining: 1m 1s
832: learn: 0.4130865 test: 0.4223153 best: 0.4223153 (832) total: 5m 6s remaining: 1m 1s
833: learn: 0.4130787 test: 0.4223075 best: 0.4223075 (833) total: 5m 7s remaining: 1m 1s
834: learn: 0.4130777 test: 0.4223067 best: 0.4223067 (834) total: 5m 7s remaining: 1m
835: learn: 0.4130484 test: 0.4222946 best: 0.4222946 (835) total: 5m 8s remaining: 1m
836: learn: 0.4129761 test: 0.4222994 best: 0.4222946 (835) total: 5m 8s remaining: 1m
837: learn: 0.4129738 test: 0.4222957 best: 0.4222946 (835) total: 5m 8s remaining: 59.7s
838: learn: 0.4129419 test: 0.4222777 best: 0.4222777 (838) total: 5m 9s remaining: 59.3s
839: learn: 0.4129414 test: 0.4222769 best: 0.4222769 (839) total: 5m 9s remaining: 58.9s
840: learn: 0.4129148 test: 0.4222653 best: 0.4222653 (840) total: 5m 9s remaining: 58.5s
841: learn: 0.4129003 test: 0.4222616 best: 0.4222616 (841) total: 5m 10s remaining: 58.2s
842: learn: 0.4128448 test: 0.4222403 best: 0.4222403 (842) total: 5m 10s remaining: 57.8s
843: learn: 0.4128057 test: 0.4222365 best: 0.4222365 (843) total: 5m 11s remaining: 57.5s
844: learn: 0.4127844 test: 0.4222290 best: 0.4222290 (844) total: 5m 11s remaining: 57.1s
845: learn: 0.4127731 test: 0.4222259 best: 0.4222259 (845) total: 5m 11s remaining: 56.8s
846: learn: 0.4127414 test: 0.4222122 best: 0.4222122 (846) total: 5m 12s remaining: 56.4s
847: learn: 0.4127086 test: 0.4222035 best: 0.4222035 (847) total: 5m 12s remaining: 56s
848: learn: 0.4127076 test: 0.4222031 best: 0.4222031 (848) total: 5m 12s remaining: 55.6s
849: learn: 0.4126837 test: 0.4221969 best: 0.4221969 (849) total: 5m 13s remaining: 55.3s
850: learn: 0.4126587 test: 0.4221783 best: 0.4221783 (850) total: 5m 13s remaining: 54.9s
851: learn: 0.4126571 test: 0.4221764 best: 0.4221764 (851) total: 5m 13s remaining: 54.5s
852: learn: 0.4126571 test: 0.4221764 best: 0.4221764 (852) total: 5m 13s remaining: 54.1s
853: learn: 0.4126388 test: 0.4221669 best: 0.4221669 (853) total: 5m 14s remaining: 53.8s
854: learn: 0.4125723 test: 0.4221554 best: 0.4221554 (854) total: 5m 14s remaining: 53.4s
855: learn: 0.4125501 test: 0.4221390 best: 0.4221390 (855) total: 5m 15s remaining: 53s
856: learn: 0.4125376 test: 0.4221367 best: 0.4221367 (856) total: 5m 15s remaining: 52.7s
857: learn: 0.4124901 test: 0.4221136 best: 0.4221136 (857) total: 5m 16s remaining: 52.3s
858: learn: 0.4124856 test: 0.4221101 best: 0.4221101 (858) total: 5m 16s remaining: 51.9s
859: learn: 0.4124581 test: 0.4220952 best: 0.4220952 (859) total: 5m 16s remaining: 51.6s
860: learn: 0.4124243 test: 0.4220840 best: 0.4220840 (860) total: 5m 17s remaining: 51.3s
861: learn: 0.4124081 test: 0.4220719 best: 0.4220719 (861) total: 5m 18s remaining: 50.9s
862: learn: 0.4123984 test: 0.4220666 best: 0.4220666 (862) total: 5m 18s remaining: 50.5s
863: learn: 0.4123912 test: 0.4220654 best: 0.4220654 (863) total: 5m 18s remaining: 50.1s
864: learn: 0.4123816 test: 0.4220642 best: 0.4220642 (864) total: 5m 18s remaining: 49.8s
865: learn: 0.4123401 test: 0.4220461 best: 0.4220461 (865) total: 5m 19s remaining: 49.4s
866: learn: 0.4123235 test: 0.4220404 best: 0.4220404 (866) total: 5m 19s remaining: 49.1s
867: learn: 0.4122761 test: 0.4220259 best: 0.4220259 (867) total: 5m 20s remaining: 48.7s
868: learn: 0.4122560 test: 0.4220170 best: 0.4220170 (868) total: 5m 20s remaining: 48.4s
869: learn: 0.4122374 test: 0.4220108 best: 0.4220108 (869) total: 5m 21s remaining: 48s
870: learn: 0.4121959 test: 0.4219916 best: 0.4219916 (870) total: 5m 21s remaining: 47.6s
871: learn: 0.4121853 test: 0.4219828 best: 0.4219828 (871) total: 5m 21s remaining: 47.2s
872: learn: 0.4121686 test: 0.4219756 best: 0.4219756 (872) total: 5m 22s remaining: 46.9s
873: learn: 0.4121635 test: 0.4219703 best: 0.4219703 (873) total: 5m 22s remaining: 46.5s
874: learn: 0.4121319 test: 0.4219359 best: 0.4219359 (874) total: 5m 22s remaining: 46.1s
875: learn: 0.4120917 test: 0.4219270 best: 0.4219270 (875) total: 5m 23s remaining: 45.8s
876: learn: 0.4120475 test: 0.4219271 best: 0.4219270 (875) total: 5m 23s remaining: 45.4s
877: learn: 0.4120471 test: 0.4219267 best: 0.4219267 (877) total: 5m 23s remaining: 45s
878: learn: 0.4120176 test: 0.4219036 best: 0.4219036 (878) total: 5m 24s remaining: 44.7s
879: learn: 0.4120170 test: 0.4219032 best: 0.4219032 (879) total: 5m 24s remaining: 44.2s
880: learn: 0.4119817 test: 0.4218855 best: 0.4218855 (880) total: 5m 24s remaining: 43.9s
881: learn: 0.4119376 test: 0.4218767 best: 0.4218767 (881) total: 5m 25s remaining: 43.5s
882: learn: 0.4119162 test: 0.4218730 best: 0.4218730 (882) total: 5m 25s remaining: 43.2s
883: learn: 0.4118958 test: 0.4218658 best: 0.4218658 (883) total: 5m 26s remaining: 42.8s
884: learn: 0.4118838 test: 0.4218560 best: 0.4218560 (884) total: 5m 26s remaining: 42.4s
885: learn: 0.4118690 test: 0.4218538 best: 0.4218538 (885) total: 5m 26s remaining: 42.1s
886: learn: 0.4118516 test: 0.4218534 best: 0.4218534 (886) total: 5m 27s remaining: 41.7s
887: learn: 0.4118205 test: 0.4218384 best: 0.4218384 (887) total: 5m 27s remaining: 41.4s
888: learn: 0.4117927 test: 0.4218285 best: 0.4218285 (888) total: 5m 28s remaining: 41s
889: learn: 0.4117583 test: 0.4218223 best: 0.4218223 (889) total: 5m 28s remaining: 40.6s
890: learn: 0.4117406 test: 0.4218148 best: 0.4218148 (890) total: 5m 29s remaining: 40.3s
891: learn: 0.4117253 test: 0.4218105 best: 0.4218105 (891) total: 5m 29s remaining: 39.9s
892: learn: 0.4117046 test: 0.4218095 best: 0.4218095 (892) total: 5m 30s remaining: 39.6s
893: learn: 0.4116701 test: 0.4217840 best: 0.4217840 (893) total: 5m 30s remaining: 39.2s
894: learn: 0.4116306 test: 0.4217812 best: 0.4217812 (894) total: 5m 31s remaining: 38.8s
895: learn: 0.4116116 test: 0.4217716 best: 0.4217716 (895) total: 5m 31s remaining: 38.5s
896: learn: 0.4115899 test: 0.4217681 best: 0.4217681 (896) total: 5m 32s remaining: 38.1s
897: learn: 0.4115461 test: 0.4217525 best: 0.4217525 (897) total: 5m 32s remaining: 37.8s
898: learn: 0.4115342 test: 0.4217524 best: 0.4217524 (898) total: 5m 33s remaining: 37.4s
899: learn: 0.4114892 test: 0.4217425 best: 0.4217425 (899) total: 5m 33s remaining: 37.1s
900: learn: 0.4114684 test: 0.4217310 best: 0.4217310 (900) total: 5m 33s remaining: 36.7s
901: learn: 0.4114463 test: 0.4217071 best: 0.4217071 (901) total: 5m 34s remaining: 36.3s
902: learn: 0.4114351 test: 0.4217021 best: 0.4217021 (902) total: 5m 34s remaining: 35.9s
903: learn: 0.4114080 test: 0.4216872 best: 0.4216872 (903) total: 5m 35s remaining: 35.6s
904: learn: 0.4113972 test: 0.4216844 best: 0.4216844 (904) total: 5m 35s remaining: 35.2s
905: learn: 0.4113848 test: 0.4216809 best: 0.4216809 (905) total: 5m 35s remaining: 34.8s
906: learn: 0.4113714 test: 0.4216763 best: 0.4216763 (906) total: 5m 36s remaining: 34.5s
907: learn: 0.4113544 test: 0.4216644 best: 0.4216644 (907) total: 5m 36s remaining: 34.1s
908: learn: 0.4113526 test: 0.4216638 best: 0.4216638 (908) total: 5m 36s remaining: 33.7s
909: learn: 0.4113509 test: 0.4216625 best: 0.4216625 (909) total: 5m 36s remaining: 33.3s
910: learn: 0.4113034 test: 0.4216575 best: 0.4216575 (910) total: 5m 37s remaining: 33s
911: learn: 0.4113028 test: 0.4216576 best: 0.4216575 (910) total: 5m 37s remaining: 32.6s
912: learn: 0.4112814 test: 0.4216489 best: 0.4216489 (912) total: 5m 38s remaining: 32.2s
913: learn: 0.4112370 test: 0.4216275 best: 0.4216275 (913) total: 5m 38s remaining: 31.8s
914: learn: 0.4112335 test: 0.4216254 best: 0.4216254 (914) total: 5m 38s remaining: 31.4s
915: learn: 0.4111630 test: 0.4215720 best: 0.4215720 (915) total: 5m 38s remaining: 31.1s
916: learn: 0.4111451 test: 0.4215648 best: 0.4215648 (916) total: 5m 39s remaining: 30.7s
917: learn: 0.4111132 test: 0.4215596 best: 0.4215596 (917) total: 5m 39s remaining: 30.4s
918: learn: 0.4111077 test: 0.4215543 best: 0.4215543 (918) total: 5m 40s remaining: 30s
919: learn: 0.4111051 test: 0.4215535 best: 0.4215535 (919) total: 5m 40s remaining: 29.6s
920: learn: 0.4110967 test: 0.4215454 best: 0.4215454 (920) total: 5m 40s remaining: 29.2s
921: learn: 0.4110425 test: 0.4215356 best: 0.4215356 (921) total: 5m 40s remaining: 28.8s
922: learn: 0.4110394 test: 0.4215320 best: 0.4215320 (922) total: 5m 41s remaining: 28.5s
923: learn: 0.4110394 test: 0.4215320 best: 0.4215320 (923) total: 5m 41s remaining: 28.1s
924: learn: 0.4110027 test: 0.4215056 best: 0.4215056 (924) total: 5m 41s remaining: 27.7s
925: learn: 0.4109833 test: 0.4214958 best: 0.4214958 (925) total: 5m 42s remaining: 27.3s
926: learn: 0.4109579 test: 0.4214937 best: 0.4214937 (926) total: 5m 42s remaining: 27s
927: learn: 0.4109573 test: 0.4214929 best: 0.4214929 (927) total: 5m 42s remaining: 26.6s
928: learn: 0.4109059 test: 0.4214767 best: 0.4214767 (928) total: 5m 43s remaining: 26.2s
929: learn: 0.4108401 test: 0.4214658 best: 0.4214658 (929) total: 5m 43s remaining: 25.9s
930: learn: 0.4108393 test: 0.4214640 best: 0.4214640 (930) total: 5m 43s remaining: 25.5s
931: learn: 0.4108114 test: 0.4214513 best: 0.4214513 (931) total: 5m 44s remaining: 25.1s
932: learn: 0.4107621 test: 0.4214358 best: 0.4214358 (932) total: 5m 44s remaining: 24.8s
933: learn: 0.4107359 test: 0.4214225 best: 0.4214225 (933) total: 5m 45s remaining: 24.4s
934: learn: 0.4107189 test: 0.4214057 best: 0.4214057 (934) total: 5m 45s remaining: 24s
935: learn: 0.4107119 test: 0.4214039 best: 0.4214039 (935) total: 5m 46s remaining: 23.7s
936: learn: 0.4107044 test: 0.4214001 best: 0.4214001 (936) total: 5m 46s remaining: 23.3s
937: learn: 0.4106956 test: 0.4213944 best: 0.4213944 (937) total: 5m 46s remaining: 22.9s
938: learn: 0.4106305 test: 0.4213867 best: 0.4213867 (938) total: 5m 47s remaining: 22.6s
939: learn: 0.4106217 test: 0.4213820 best: 0.4213820 (939) total: 5m 47s remaining: 22.2s
940: learn: 0.4106216 test: 0.4213819 best: 0.4213819 (940) total: 5m 47s remaining: 21.8s
941: learn: 0.4106090 test: 0.4213794 best: 0.4213794 (941) total: 5m 47s remaining: 21.4s
942: learn: 0.4105481 test: 0.4213611 best: 0.4213611 (942) total: 5m 48s remaining: 21.1s
943: learn: 0.4105179 test: 0.4213516 best: 0.4213516 (943) total: 5m 48s remaining: 20.7s
944: learn: 0.4104881 test: 0.4213416 best: 0.4213416 (944) total: 5m 49s remaining: 20.3s
945: learn: 0.4104582 test: 0.4213331 best: 0.4213331 (945) total: 5m 49s remaining: 20s
946: learn: 0.4104456 test: 0.4213266 best: 0.4213266 (946) total: 5m 50s remaining: 19.6s
947: learn: 0.4103928 test: 0.4213099 best: 0.4213099 (947) total: 5m 50s remaining: 19.2s
948: learn: 0.4103784 test: 0.4213052 best: 0.4213052 (948) total: 5m 51s remaining: 18.9s
949: learn: 0.4103784 test: 0.4213051 best: 0.4213051 (949) total: 5m 51s remaining: 18.5s
950: learn: 0.4103765 test: 0.4213036 best: 0.4213036 (950) total: 5m 51s remaining: 18.1s
951: learn: 0.4103765 test: 0.4213035 best: 0.4213035 (951) total: 5m 51s remaining: 17.7s
952: learn: 0.4103732 test: 0.4212996 best: 0.4212996 (952) total: 5m 51s remaining: 17.3s
953: learn: 0.4103728 test: 0.4212990 best: 0.4212990 (953) total: 5m 51s remaining: 16.9s
954: learn: 0.4103483 test: 0.4212894 best: 0.4212894 (954) total: 5m 51s remaining: 16.6s
955: learn: 0.4103276 test: 0.4212861 best: 0.4212861 (955) total: 5m 52s remaining: 16.2s
956: learn: 0.4103242 test: 0.4212827 best: 0.4212827 (956) total: 5m 52s remaining: 15.8s
957: learn: 0.4102827 test: 0.4212774 best: 0.4212774 (957) total: 5m 53s remaining: 15.5s
958: learn: 0.4102638 test: 0.4212666 best: 0.4212666 (958) total: 5m 53s remaining: 15.1s
959: learn: 0.4102167 test: 0.4212566 best: 0.4212566 (959) total: 5m 54s remaining: 14.8s
960: learn: 0.4102071 test: 0.4212561 best: 0.4212561 (960) total: 5m 54s remaining: 14.4s
961: learn: 0.4101575 test: 0.4212007 best: 0.4212007 (961) total: 5m 54s remaining: 14s
962: learn: 0.4101516 test: 0.4211953 best: 0.4211953 (962) total: 5m 55s remaining: 13.7s
963: learn: 0.4101515 test: 0.4211953 best: 0.4211953 (963) total: 5m 55s remaining: 13.3s
964: learn: 0.4101413 test: 0.4211920 best: 0.4211920 (964) total: 5m 55s remaining: 12.9s
965: learn: 0.4100822 test: 0.4211588 best: 0.4211588 (965) total: 5m 56s remaining: 12.5s
966: learn: 0.4100803 test: 0.4211566 best: 0.4211566 (966) total: 5m 56s remaining: 12.2s
967: learn: 0.4100789 test: 0.4211549 best: 0.4211549 (967) total: 5m 56s remaining: 11.8s
968: learn: 0.4100457 test: 0.4211503 best: 0.4211503 (968) total: 5m 57s remaining: 11.4s
969: learn: 0.4100257 test: 0.4211434 best: 0.4211434 (969) total: 5m 57s remaining: 11.1s
970: learn: 0.4100256 test: 0.4211432 best: 0.4211432 (970) total: 5m 57s remaining: 10.7s
971: learn: 0.4099873 test: 0.4211227 best: 0.4211227 (971) total: 5m 58s remaining: 10.3s
972: learn: 0.4099473 test: 0.4210973 best: 0.4210973 (972) total: 5m 58s remaining: 9.95s
973: learn: 0.4099454 test: 0.4210967 best: 0.4210967 (973) total: 5m 58s remaining: 9.58s
974: learn: 0.4099162 test: 0.4210821 best: 0.4210821 (974) total: 5m 59s remaining: 9.21s
975: learn: 0.4098868 test: 0.4210797 best: 0.4210797 (975) total: 5m 59s remaining: 8.84s
976: learn: 0.4098857 test: 0.4210793 best: 0.4210793 (976) total: 5m 59s remaining: 8.47s
977: learn: 0.4098305 test: 0.4210665 best: 0.4210665 (977) total: 6m remaining: 8.11s
978: learn: 0.4098245 test: 0.4210628 best: 0.4210628 (978) total: 6m remaining: 7.74s
979: learn: 0.4098117 test: 0.4210537 best: 0.4210537 (979) total: 6m 1s remaining: 7.37s
980: learn: 0.4097902 test: 0.4210471 best: 0.4210471 (980) total: 6m 1s remaining: 7.01s
981: learn: 0.4097710 test: 0.4210444 best: 0.4210444 (981) total: 6m 2s remaining: 6.64s
982: learn: 0.4097464 test: 0.4210346 best: 0.4210346 (982) total: 6m 2s remaining: 6.27s
983: learn: 0.4097441 test: 0.4210317 best: 0.4210317 (983) total: 6m 2s remaining: 5.9s
984: learn: 0.4097034 test: 0.4210246 best: 0.4210246 (984) total: 6m 3s remaining: 5.53s
985: learn: 0.4096907 test: 0.4210169 best: 0.4210169 (985) total: 6m 3s remaining: 5.17s
986: learn: 0.4096545 test: 0.4210052 best: 0.4210052 (986) total: 6m 4s remaining: 4.8s
987: learn: 0.4096464 test: 0.4210014 best: 0.4210014 (987) total: 6m 4s remaining: 4.43s
988: learn: 0.4096129 test: 0.4210014 best: 0.4210014 (988) total: 6m 5s remaining: 4.06s
989: learn: 0.4096105 test: 0.4210009 best: 0.4210009 (989) total: 6m 5s remaining: 3.69s
990: learn: 0.4095879 test: 0.4209969 best: 0.4209969 (990) total: 6m 5s remaining: 3.32s
991: learn: 0.4095452 test: 0.4209793 best: 0.4209793 (991) total: 6m 6s remaining: 2.95s
992: learn: 0.4094860 test: 0.4209690 best: 0.4209690 (992) total: 6m 6s remaining: 2.58s
993: learn: 0.4094672 test: 0.4209498 best: 0.4209498 (993) total: 6m 6s remaining: 2.21s
994: learn: 0.4094380 test: 0.4209391 best: 0.4209391 (994) total: 6m 7s remaining: 1.85s
995: learn: 0.4094061 test: 0.4209269 best: 0.4209269 (995) total: 6m 7s remaining: 1.48s
996: learn: 0.4094028 test: 0.4209259 best: 0.4209259 (996) total: 6m 8s remaining: 1.11s
997: learn: 0.4093776 test: 0.4209150 best: 0.4209150 (997) total: 6m 8s remaining: 739ms
998: learn: 0.4093341 test: 0.4208834 best: 0.4208834 (998) total: 6m 8s remaining: 369ms
999: learn: 0.4092981 test: 0.4208687 best: 0.4208687 (999) total: 6m 9s remaining: 0us
bestTest = 0.4208686696
bestIteration = 999
Out[69]:
<catboost.core.CatBoostClassifier at 0x2048192cda0>
In [70]:
prediction_proba = model.predict_proba(df_test)[:,1]
In [71]:
model.get_feature_importance(X_train,y_train,cat_features=categorical_features_indices)
Out[71]:
[2.4904738937880913,
0.9023635736328831,
26.784972512305057,
3.474099618979113,
2.489420620267185,
4.015760514421802,
3.6905698914829443,
6.242727532021042,
3.7215939749033424,
4.357634070441675,
3.5198557625898284,
6.269741184129969,
5.607910307964413,
1.9890194408451036,
18.474678710283758,
2.991705877361596,
2.528727859987967,
0.4487446545942221]
In [72]:
pd.Series(prediction_proba,
name='dep_delayed_15min').to_csv(f'{PATH}cat_encoded_flights_ods.csv',
index_label='id', header=True)
In [77]:
# This way we have randomness and are able to reproduce the behaviour within this cell.
np.random.seed(13)
from sklearn.model_selection import KFold
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 = 10
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
In [81]:
features = df_raw.columns
numeric_features = []
categorical_features = []
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)
else:
numeric_features.append(feature)
categorical_features
Out[81]:
['Month', 'DayofMonth', 'DayOfWeek', 'UniqueCarrier', 'Origin', 'Dest']
In [88]:
df_raw['target'] = y.map({'Y': 1, 'N': 0}).values
In [90]:
%%time
# Apply the encoding to training and test data, and preserve the mapping
impact_coding_map = {}
for f in categorical_features:
print("Impact coding for {}".format(f))
df_raw["impact_encoded_{}".format(f)], impact_coding_mapping, default_coding = impact_coding(df_raw, f,'target')
impact_coding_map[f] = (impact_coding_mapping, default_coding)
mapping, default_mean = impact_coding_map[f]
df_test["impact_encoded_{}".format(f)] = df_test.apply(lambda x: mapping[x[f]]
if x[f] in mapping
else default_mean
, axis=1)
df_raw.to_csv(PATH + '\\impact_encoded_train.csv',index = False)
df_test.to_csv(PATH + '\\impact_encoded_test.csv',index = False)
Impact coding for Month
Impact coding for DayofMonth
Impact coding for DayOfWeek
Impact coding for UniqueCarrier
Impact coding for Origin
Impact coding for Dest
Wall time: 13min 44s
In [6]:
!dir {PATH}
Volume in drive D is Local Disk
Volume Serial Number is B408-A348
Directory of D:\Github\fastai\courses\ml1\AV_Mckin\ods
21-Apr-18 10:54 AM <DIR> .
21-Apr-18 10:54 AM <DIR> ..
18-Apr-18 08:21 AM <DIR> .ipynb_checkpoints
09-Apr-18 02:55 PM 30,203,258 add_test_dummies.csv
09-Apr-18 02:58 PM 35,412,316 add_test_dummiesv2.csv
09-Apr-18 02:55 PM 92,576,888 add_train_dummies.csv
09-Apr-18 02:58 PM 109,333,024 add_train_dummiesv2.csv
13-Apr-18 12:43 PM 2,659,732 cat_encoded_flights_ods.csv
07-Feb-18 08:21 PM 1,800,682 site_dic.pkl
21-Apr-18 10:09 AM 2,407,429 sub-210418.csv
21-Apr-18 10:09 AM 2,407,429 sub1.csv
17-Mar-18 11:25 PM 19,450,729 websites_test_sessions.csv
17-Mar-18 11:30 PM 60,526,801 websites_train_sessions.csv
10 File(s) 356,778,288 bytes
3 Dir(s) 183,789,621,248 bytes free
In [32]:
sub_df1 = pd.read_csv(f'{PATH}cat_encoded_flights_ods.csv');
sub_df2 = pd.read_csv(f'{PATH}cat_encoded_flights_ods.csv');
In [61]:
preds = (sub_df1.dep_delayed_15min * 1.3 + sub_df2.dep_delayed_15min*2.5)/4
In [62]:
max(preds)
Out[62]:
0.90939239921497128
In [63]:
preds1 = np.where(preds>.80, .84, preds)
In [64]:
sub_df['dep_delayed_15min'] = preds
In [65]:
sub_df.to_csv(f'{PATH}modified_flights.csv',index=None,)
In [ ]:
Content source: AdityaSoni19031997/Machine-Learning
Similar notebooks:
notebook.community | gallery | about