8918 6892 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,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier) sklearn.pipeline.Pipeline 2 openml==0.8.0dev,sklearn==0.20.2 Automatically created scikit-learn flow. 2019-01-17T18:43:04 English sklearn==0.20.2 numpy>=1.6.1 scipy>=0.9 memory null steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "variancethreshold", "step_name": "variancethreshold"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "randomforestclassifier", "step_name": "randomforestclassifier"}}] columntransformer 8891 6892 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)) sklearn.compose._column_transformer.ColumnTransformer 3 openml==0.8.0dev,sklearn==0.20.2 Automatically created scikit-learn flow. 2019-01-05T00:58:40 English sklearn==0.20.2 numpy>=1.6.1 scipy>=0.9 n_jobs null remainder "passthrough" sparse_threshold 0.3 transformer_weights null transformers [{"oml-python:serialized_object": "component_reference", "value": {"key": "numeric", "step_name": "numeric", "argument_1": []}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "nominal", "step_name": "nominal", "argument_1": [0, 1, 2, 3]}}] numeric 8892 6892 sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler) sklearn.pipeline.Pipeline 3 openml==0.8.0dev,sklearn==0.20.2 Automatically created scikit-learn flow. 2019-01-05T00:58:40 English sklearn==0.20.2 numpy>=1.6.1 scipy>=0.9 memory null steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "imputer", "step_name": "imputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}] imputer 8893 6892 sklearn.preprocessing.imputation.Imputer sklearn.preprocessing.imputation.Imputer 34 openml==0.8.0dev,sklearn==0.20.2 Automatically created scikit-learn flow. 2019-01-05T00:58:40 English sklearn==0.20.2 numpy>=1.6.1 scipy>=0.9 axis 0 copy true missing_values "NaN" strategy "median" verbose 0 openml-python python scikit-learn sklearn sklearn_0.20.2 standardscaler 8894 6892 sklearn.preprocessing.data.StandardScaler sklearn.preprocessing.data.StandardScaler 20 openml==0.8.0dev,sklearn==0.20.2 Automatically created scikit-learn flow. 2019-01-05T00:58:40 English sklearn==0.20.2 numpy>=1.6.1 scipy>=0.9 copy true with_mean true with_std true openml-python python scikit-learn sklearn sklearn_0.20.2 openml-python python scikit-learn sklearn sklearn_0.20.2 nominal 8895 6892 sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder) sklearn.pipeline.Pipeline 3 openml==0.8.0dev,sklearn==0.20.2 Automatically created scikit-learn flow. 2019-01-05T00:58:40 English sklearn==0.20.2 numpy>=1.6.1 scipy>=0.9 memory null steps [{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}] simpleimputer 8896 6892 sklearn.impute.SimpleImputer sklearn.impute.SimpleImputer 6 openml==0.8.0dev,sklearn==0.20.2 Automatically created scikit-learn flow. 2019-01-05T00:58:40 English sklearn==0.20.2 numpy>=1.6.1 scipy>=0.9 copy true fill_value -1 missing_values NaN strategy "constant" verbose 0 openml-python python scikit-learn sklearn sklearn_0.20.2 onehotencoder 8897 6892 sklearn.preprocessing._encoders.OneHotEncoder sklearn.preprocessing._encoders.OneHotEncoder 6 openml==0.8.0dev,sklearn==0.20.2 Automatically created scikit-learn flow. 2019-01-05T00:58:40 English sklearn==0.20.2 numpy>=1.6.1 scipy>=0.9 categorical_features null categories null dtype {"oml-python:serialized_object": "type", "value": "np.float64"} handle_unknown "ignore" n_values null sparse true openml-python python scikit-learn sklearn sklearn_0.20.2 openml-python python scikit-learn sklearn sklearn_0.20.2 openml-python python scikit-learn sklearn sklearn_0.20.2 variancethreshold 8898 6892 sklearn.feature_selection.variance_threshold.VarianceThreshold sklearn.feature_selection.variance_threshold.VarianceThreshold 21 openml==0.8.0dev,sklearn==0.20.2 Automatically created scikit-learn flow. 2019-01-05T00:58:40 English sklearn==0.20.2 numpy>=1.6.1 scipy>=0.9 threshold 0.0 openml-python python scikit-learn sklearn sklearn_0.20.2 randomforestclassifier 8919 6892 sklearn.ensemble.forest.RandomForestClassifier sklearn.ensemble.forest.RandomForestClassifier 48 openml==0.8.0dev,sklearn==0.20.2 Automatically created scikit-learn flow. 2019-01-17T18:43:04 English sklearn==0.20.2 numpy>=1.6.1 scipy>=0.9 bootstrap false class_weight null criterion "gini" max_depth null max_features 0.267441246822437 max_leaf_nodes null min_impurity_decrease 0.0 min_impurity_split null min_samples_leaf 6 min_samples_split 7 min_weight_fraction_leaf 0.0 n_estimators 100 n_jobs null oob_score false random_state null verbose 0 warm_start false openml-python python scikit-learn sklearn sklearn_0.20.2 openml-python python scikit-learn sklearn sklearn_0.20.2