5732 2514 sklearn.pipeline.Pipeline(steps__standardscaler=sklearn.preprocessing.data.StandardScaler,steps__votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifier(estimators__extra=sklearn.ensemble.forest.ExtraTreesClassifier,estimators__rf=sklearn.ensemble.forest.RandomForestClassifier,estimators__gradboost=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,estimators__xgboost=xgboost.sklearn.XGBClassifier)) sklearn.pipeline.Pipeline 1 sklearn==0.18.1,xgboost==0.6 Automatically created sub-component. 2017-03-12T05:16:51 English sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "steps__standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "steps__votingclassifier", "step_name": "votingclassifier"}}] steps__standardscaler 5660 2617 sklearn.preprocessing.data.StandardScaler sklearn.preprocessing.data.StandardScaler 1 sklearn==0.18.1 Automatically created sub-component. 2017-03-07T19:08:03 English sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 copy true with_mean true with_std true steps__votingclassifier 5731 2514 sklearn.ensemble.voting_classifier.VotingClassifier(estimators__extra=sklearn.ensemble.forest.ExtraTreesClassifier,estimators__rf=sklearn.ensemble.forest.RandomForestClassifier,estimators__gradboost=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,estimators__xgboost=xgboost.sklearn.XGBClassifier) sklearn.ensemble.voting_classifier.VotingClassifier 1 sklearn==0.18.1,xgboost==0.6 Automatically created sub-component. 2017-03-12T04:34:45 English sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 estimators [{"oml-python:serialized_object": "component_reference", "value": {"key": "estimators__extra", "step_name": "extra"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimators__rf", "step_name": "rf"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimators__gradboost", "step_name": "gradboost"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "estimators__xgboost", "step_name": "xgboost"}}] n_jobs 1 voting "soft" weights null estimators__rf 5500 762 sklearn.ensemble.forest.RandomForestClassifier sklearn.ensemble.forest.RandomForestClassifier 16 sklearn==0.18.1 Automatically created sub-component. 2017-02-23T15:33:12 English sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 bootstrap true class_weight null criterion "gini" max_depth null max_features "auto" max_leaf_nodes null min_impurity_split 1e-07 min_samples_leaf 1 min_samples_split 2 min_weight_fraction_leaf 0.0 n_estimators 10 n_jobs 1 oob_score false random_state null verbose 0 warm_start false study_73 Verified_Learning_Curve,Verified_Supervised_Classification estimators__xgboost 5521 1936 xgboost.sklearn.XGBClassifier xgboost.sklearn.XGBClassifier 3 xgboost==0.6 Automatically created sub-component. 2017-02-27T13:22:04 English sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 base_score 0.5 colsample_bylevel 1 colsample_bytree 1 gamma 0 learning_rate 0.1 max_delta_step 0 max_depth 3 min_child_weight 1 missing null n_estimators 100 nthread -1 objective "binary:logistic" reg_alpha 0 reg_lambda 1 scale_pos_weight 1 seed 0 silent true subsample 1 Verified_Supervised_Classification estimators__extra 5604 2568 sklearn.ensemble.forest.ExtraTreesClassifier sklearn.ensemble.forest.ExtraTreesClassifier 5 sklearn==0.18.1 Automatically created sub-component. 2017-03-02T23:49:17 English sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 bootstrap false class_weight null criterion "gini" max_depth null max_features "auto" max_leaf_nodes null 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 null verbose 0 warm_start false Verified_Supervised_Classification estimators__gradboost 5626 2568 sklearn.ensemble.gradient_boosting.GradientBoostingClassifier sklearn.ensemble.gradient_boosting.GradientBoostingClassifier 3 sklearn==0.18.1 Automatically created sub-component. 2017-03-03T12:47:56 English sklearn==0.18.1 numpy>=1.6.1 scipy>=0.9 criterion "friedman_mse" init null learning_rate 0.05 loss "deviance" max_depth 6 max_features null max_leaf_nodes null min_impurity_split 1e-07 min_samples_leaf 1 min_samples_split 2 min_weight_fraction_leaf 0.0 n_estimators 50 presort "auto" random_state null subsample 0.5 verbose 0 warm_start false Verified_Supervised_Classification