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Task 14965 (Supervised Classification) bank-marketing Uploaded 14-12-2018 by Scikit-learn Bot
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.pr eprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.St andardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.imput e.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder )),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceT hreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.Grad ientBoostingClassifier)(1)	Automatically created scikit-learn flow.
sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)_memory	null
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(2)_n_jobs	null
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(2)_remainder	"passthrough"
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(2)_sparse_threshold	0.3
sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(2)_transformer_weights	null
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler)(2)_memory	null
sklearn.preprocessing.imputation.Imputer(31)_axis	0
sklearn.preprocessing.imputation.Imputer(31)_copy	true
sklearn.preprocessing.imputation.Imputer(31)_missing_values	"NaN"
sklearn.preprocessing.imputation.Imputer(31)_strategy	"most_frequent"
sklearn.preprocessing.imputation.Imputer(31)_verbose	0
sklearn.preprocessing.data.StandardScaler(17)_copy	true
sklearn.preprocessing.data.StandardScaler(17)_with_mean	true
sklearn.preprocessing.data.StandardScaler(17)_with_std	true
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(2)_memory	null
sklearn.impute.SimpleImputer(2)_copy	true
sklearn.impute.SimpleImputer(2)_fill_value	-1
sklearn.impute.SimpleImputer(2)_missing_values	NaN
sklearn.impute.SimpleImputer(2)_strategy	"constant"
sklearn.impute.SimpleImputer(2)_verbose	0
sklearn.preprocessing._encoders.OneHotEncoder(5)_categorical_features	null
sklearn.preprocessing._encoders.OneHotEncoder(5)_categories	null
sklearn.preprocessing._encoders.OneHotEncoder(5)_dtype	{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(5)_handle_unknown	"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(5)_n_values	null
sklearn.preprocessing._encoders.OneHotEncoder(5)_sparse	true
sklearn.feature_selection.variance_threshold.VarianceThreshold(19)_threshold	0.0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_criterion	"mae"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_init	null
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_learning_rate	0.0206259757031229
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_loss	"deviance"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_max_depth	5
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_max_features	0.16360942047784155
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_max_leaf_nodes	null
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_impurity_decrease	0.6566992836726578
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_impurity_split	null
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_samples_leaf	6
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_samples_split	5
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_min_weight_fraction_leaf	0.10388853204592191
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_n_estimators	302
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_n_iter_no_change	259
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_presort	"auto"
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_random_state	56516
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_subsample	0.9330888607271957
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_tol	0.0017462357911775983
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_validation_fraction	0.03339605212518015
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_verbose	0
sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(15)_warm_start	false