Run 10429322

Task 23 (Supervised Classification) cmc Uploaded 09-12-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num =sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standa rdScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing ._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(2)	Automatically created scikit-learn flow.
sklearn.impute._base.SimpleImputer(1)_add_indicator	false
sklearn.impute._base.SimpleImputer(1)_copy	true
sklearn.impute._base.SimpleImputer(1)_fill_value	null
sklearn.impute._base.SimpleImputer(1)_missing_values	NaN
sklearn.impute._base.SimpleImputer(1)_strategy	"most_frequent"
sklearn.impute._base.SimpleImputer(1)_verbose	0
sklearn.preprocessing.data.StandardScaler(29)_copy	true
sklearn.preprocessing.data.StandardScaler(29)_with_mean	true
sklearn.preprocessing.data.StandardScaler(29)_with_std	true
sklearn.svm.classes.SVC(31)_C	82.60048604501297
sklearn.svm.classes.SVC(31)_cache_size	200
sklearn.svm.classes.SVC(31)_class_weight	null
sklearn.svm.classes.SVC(31)_coef0	0.0
sklearn.svm.classes.SVC(31)_decision_function_shape	"ovr"
sklearn.svm.classes.SVC(31)_degree	3
sklearn.svm.classes.SVC(31)_gamma	0.490328497576602
sklearn.svm.classes.SVC(31)_kernel	"rbf"
sklearn.svm.classes.SVC(31)_max_iter	-1
sklearn.svm.classes.SVC(31)_probability	true
sklearn.svm.classes.SVC(31)_random_state	1
sklearn.svm.classes.SVC(31)_shrinking	true
sklearn.svm.classes.SVC(31)_tol	0.001
sklearn.svm.classes.SVC(31)_verbose	false
sklearn.preprocessing._encoders.OneHotEncoder(11)_categorical_features	null
sklearn.preprocessing._encoders.OneHotEncoder(11)_categories	null
sklearn.preprocessing._encoders.OneHotEncoder(11)_drop	null
sklearn.preprocessing._encoders.OneHotEncoder(11)_dtype	{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(11)_handle_unknown	"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(11)_n_values	null
sklearn.preprocessing._encoders.OneHotEncoder(11)_sparse	true
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(2)_memory	null
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(2)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "columntransformer", "step_name": "columntransformer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC)(2)_verbose	false
sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(2)_n_jobs	null
sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(2)_remainder	"drop"
sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(2)_sparse_threshold	0.3
sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(2)_transformer_weights	null
sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(2)_transformers	[{"oml-python:serialized_object": "component_reference", "value": {"key": "num", "step_name": "num", "argument_1": [true, false, false, true, false, false, false, false, false]}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "cat", "step_name": "cat", "argument_1": [false, true, true, false, true, true, true, true, true]}}]
sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder))(2)_verbose	false
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler)(2)_memory	null
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler)(2)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler)(2)_verbose	false
sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(2)_memory	null
sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(2)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(2)_verbose	false