Run 1852413

Task 145677 (Supervised Classification) Bioresponse Uploaded 13-03-2017 by Joost Visser
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Flow

sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standar dScaler,votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifie r(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ens emble.gradient_boosting.GradientBoostingClassifier,n_jobs=xgboost.sklearn.X GBClassifier))(1)	Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(16)_bootstrap	True
sklearn.ensemble.forest.RandomForestClassifier(16)_class_weight	None
sklearn.ensemble.forest.RandomForestClassifier(16)_criterion	entropy
sklearn.ensemble.forest.RandomForestClassifier(16)_max_depth	None
sklearn.ensemble.forest.RandomForestClassifier(16)_max_features	0.1
sklearn.ensemble.forest.RandomForestClassifier(16)_max_leaf_nodes	None
sklearn.ensemble.forest.RandomForestClassifier(16)_min_impurity_split	1e-07
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_leaf	2
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_split	2
sklearn.ensemble.forest.RandomForestClassifier(16)_min_weight_fraction_leaf	0.0
sklearn.ensemble.forest.RandomForestClassifier(16)_n_estimators	16
sklearn.ensemble.forest.RandomForestClassifier(16)_n_jobs	1
sklearn.ensemble.forest.RandomForestClassifier(16)_oob_score	False
sklearn.ensemble.forest.RandomForestClassifier(16)_random_state	None
sklearn.ensemble.forest.RandomForestClassifier(16)_verbose	0
sklearn.ensemble.forest.RandomForestClassifier(16)_warm_start	False
xgboost.sklearn.XGBClassifier(3)_base_score	0.5
xgboost.sklearn.XGBClassifier(3)_colsample_bylevel	1
xgboost.sklearn.XGBClassifier(3)_colsample_bytree	0.9
xgboost.sklearn.XGBClassifier(3)_gamma	0
xgboost.sklearn.XGBClassifier(3)_learning_rate	0.03
xgboost.sklearn.XGBClassifier(3)_max_delta_step	0
xgboost.sklearn.XGBClassifier(3)_max_depth	8
xgboost.sklearn.XGBClassifier(3)_min_child_weight	2
xgboost.sklearn.XGBClassifier(3)_missing	None
xgboost.sklearn.XGBClassifier(3)_n_estimators	16
xgboost.sklearn.XGBClassifier(3)_nthread	1
xgboost.sklearn.XGBClassifier(3)_objective	binary:logistic
xgboost.sklearn.XGBClassifier(3)_reg_alpha	0
xgboost.sklearn.XGBClassifier(3)_reg_lambda	1
xgboost.sklearn.XGBClassifier(3)_scale_pos_weight	1
xgboost.sklearn.XGBClassifier(3)_seed	0
xgboost.sklearn.XGBClassifier(3)_silent	True
xgboost.sklearn.XGBClassifier(3)_subsample	0.8
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_criterion	friedman_mse
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_init	None
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_learning_rate	0.03
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_loss	deviance
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_depth	8
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_features	sqrt
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_max_leaf_nodes	None
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_impurity_split	1e-07
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_samples_leaf	2
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_samples_split	2
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_min_weight_fraction_leaf	0.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_n_estimators	16
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_presort	auto
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_random_state	None
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_subsample	1.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_verbose	0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)_warm_start	False
sklearn.preprocessing.data.StandardScaler(1)_copy	True
sklearn.preprocessing.data.StandardScaler(1)_with_mean	True
sklearn.preprocessing.data.StandardScaler(1)_with_std	True
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=xgboost.sklearn.XGBClassifier))(1)_steps	[('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('votingclassifier', VotingClassifier(estimators=[('voting', RandomForestClassifier(bootstrap=True, class_weight=None, criterion='entropy', max_depth=None, max_features=0.1, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=2, min_samples_split=2, min_weight_fraction_leaf=0.0, ...gistic', reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=0, silent=True, subsample=0.8))], n_jobs=-1, voting='soft', weights=None))]
sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=xgboost.sklearn.XGBClassifier)(1)_estimators	[('voting', RandomForestClassifier(bootstrap=True, class_weight=None, criterion='entropy', max_depth=None, max_features=0.1, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=2, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=16, n_jobs=1, oob_score=False, random_state=None, verbose=0, warm_start=False)), ('weights', GradientBoostingClassifier(criterion='friedman_mse', init=None, learning_rate=0.03, loss='deviance', max_depth=8, max_features='sqrt', max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=2, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=16, presort='auto', random_state=None, subsample=1.0, verbose=0, warm_start=False)), ('n_jobs', XGBClassifier(base_score=0.5, colsample_bylevel=1, colsample_bytree=0.9, gamma=0, learning_rate=0.03, max_delta_step=0, max_depth=8, min_child_weight=2, mi
sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=xgboost.sklearn.XGBClassifier)(1)_n_jobs	XGBClassifier(base_score=0.5, colsample_bylevel=1, colsample_bytree=0.9, gamma=0, learning_rate=0.03, max_delta_step=0, max_depth=8, min_child_weight=2, missing=None, n_estimators=16, nthread=1, objective='binary:logistic', reg_alpha=0, reg_lambda=1, scale_pos_weight=1, seed=0, silent=True, subsample=0.8)
sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=xgboost.sklearn.XGBClassifier)(1)_voting	RandomForestClassifier(bootstrap=True, class_weight=None, criterion='entropy', max_depth=None, max_features=0.1, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=2, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=16, n_jobs=1, oob_score=False, random_state=None, verbose=0, warm_start=False)
sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=xgboost.sklearn.XGBClassifier)(1)_weights	GradientBoostingClassifier(criterion='friedman_mse', init=None, learning_rate=0.03, loss='deviance', max_depth=8, max_features='sqrt', max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=2, min_samples_split=2, min_weight_fraction_leaf=0.0, n_estimators=16, presort='auto', random_state=None, subsample=1.0, verbose=0, warm_start=False)