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03_log_example.txt
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03_log_example.txt
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vecstack log [2018.02.01].[15.41.41].305268.0eadc0
task: [classification]
n_classes: [3]
metric: [log_loss]
mode: [oof_pred]
n_models: [7]
----------------------------------------
model 0: [GaussianNB]
----------------------------------------
priors None
fold 0: [0.65551778]
fold 1: [0.42335961]
fold 2: [0.38132309]
fold 3: [0.57180128]
fold 4: [0.30426116]
----
MEAN: [0.46725258] + [0.12825825]
FULL: [0.46842847]
----------------------------------------
model 1: [LogisticRegression]
----------------------------------------
C 1.0
class_weight None
dual False
fit_intercept True
intercept_scaling 1
max_iter 100
multi_class ovr
n_jobs 1
penalty l2
random_state 0
solver liblinear
tol 0.0001
verbose 0
warm_start False
fold 0: [0.59821304]
fold 1: [0.54202039]
fold 2: [0.55194968]
fold 3: [0.46887313]
fold 4: [0.44995007]
----
MEAN: [0.52220126] + [0.05499033]
FULL: [0.52280210]
----------------------------------------
model 2: [ExtraTreesClassifier]
----------------------------------------
bootstrap False
class_weight None
criterion gini
max_depth 3
max_features auto
max_leaf_nodes None
min_impurity_split 1e-07
min_samples_leaf 1
min_samples_split 2
min_weight_fraction_leaf 0.0
n_estimators 100
n_jobs -1
oob_score False
random_state 0
verbose 0
warm_start False
fold 0: [0.79961086]
fold 1: [0.75093790]
fold 2: [0.77930597]
fold 3: [0.76984042]
fold 4: [0.75288684]
----
MEAN: [0.77051640] + [0.01799067]
FULL: [0.77062834]
----------------------------------------
model 3: [RandomForestClassifier]
----------------------------------------
bootstrap True
class_weight None
criterion gini
max_depth 3
max_features auto
max_leaf_nodes None
min_impurity_split 1e-07
min_samples_leaf 1
min_samples_split 2
min_weight_fraction_leaf 0.0
n_estimators 100
n_jobs -1
oob_score False
random_state 0
verbose 0
warm_start False
fold 0: [0.61575788]
fold 1: [0.40598536]
fold 2: [0.37631065]
fold 3: [0.48927717]
fold 4: [0.35383760]
----
MEAN: [0.44823373] + [0.09551690]
FULL: [0.44901890]
----------------------------------------
model 4: [XGBClassifier]
----------------------------------------
base_score 0.5
booster gbtree
colsample_bylevel 1
colsample_bytree 1
gamma 0
learning_rate 0.1
max_delta_step 0
max_depth 3
min_child_weight 1
missing None
n_estimators 100
n_jobs -1
nthread None
objective binary:logistic
random_state 0
reg_alpha 0
reg_lambda 1
scale_pos_weight 1
seed None
silent True
subsample 1
fold 0: [0.79844773]
fold 1: [0.29219564]
fold 2: [0.32080725]
fold 3: [0.47567222]
fold 4: [0.28695253]
----
MEAN: [0.43481507] + [0.19447336]
FULL: [0.43610692]
----------------------------------------
model 5: [LGBMClassifier]
----------------------------------------
boosting_type gbdt
class_weight None
colsample_bytree 1.0
learning_rate 0.1
max_depth 3
min_child_samples 20
min_child_weight 0.001
min_split_gain 0.0
n_estimators 100
n_jobs -1
num_leaves 31
objective None
random_state 0
reg_alpha 0.0
reg_lambda 0.0
silent True
subsample 1.0
subsample_for_bin 200000
subsample_freq 1
fold 0: [0.72121715]
fold 1: [0.28661436]
fold 2: [0.32019533]
fold 3: [0.44805274]
fold 4: [0.29008710]
----
MEAN: [0.41323334] + [0.16487562]
FULL: [0.41430248]
----------------------------------------
model 6: [KerasClassifier]
----------------------------------------
batch_size 32
build_fn <function build_keras_model_1 at 0x7f5e44659b70>
epochs 2
verbose 0
fold 0: [0.95679030]
fold 1: [0.97577886]
fold 2: [0.99147471]
fold 3: [0.97480903]
fold 4: [0.96731000]
----
MEAN: [0.97323258] + [0.01137690]
FULL: [0.97322745]
----------------------------------------
END
----------------------------------------