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Task 23 (Supervised Classification) cmc Uploaded 25-08-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transfo rmer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn .preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotenc oder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classe s.SVC)(1)	Automatically created scikit-learn flow.
sklearn.preprocessing.data.StandardScaler(30)_copy	true
sklearn.preprocessing.data.StandardScaler(30)_with_mean	true
sklearn.preprocessing.data.StandardScaler(30)_with_std	true
sklearn.svm.classes.SVC(32)_C	1.0
sklearn.svm.classes.SVC(32)_cache_size	200
sklearn.svm.classes.SVC(32)_class_weight	null
sklearn.svm.classes.SVC(32)_coef0	0.0
sklearn.svm.classes.SVC(32)_decision_function_shape	"ovr"
sklearn.svm.classes.SVC(32)_degree	3
sklearn.svm.classes.SVC(32)_gamma	"scale"
sklearn.svm.classes.SVC(32)_kernel	"rbf"
sklearn.svm.classes.SVC(32)_max_iter	-1
sklearn.svm.classes.SVC(32)_probability	false
sklearn.svm.classes.SVC(32)_random_state	45102
sklearn.svm.classes.SVC(32)_shrinking	true
sklearn.svm.classes.SVC(32)_tol	0.001
sklearn.svm.classes.SVC(32)_verbose	false
sklearn.preprocessing._encoders.OneHotEncoder(12)_categorical_features	null
sklearn.preprocessing._encoders.OneHotEncoder(12)_categories	null
sklearn.preprocessing._encoders.OneHotEncoder(12)_drop	null
sklearn.preprocessing._encoders.OneHotEncoder(12)_dtype	{"oml-python:serialized_object": "type", "value": "np.float64"}
sklearn.preprocessing._encoders.OneHotEncoder(12)_handle_unknown	"ignore"
sklearn.preprocessing._encoders.OneHotEncoder(12)_n_values	null
sklearn.preprocessing._encoders.OneHotEncoder(12)_sparse	true
sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_memory	null
sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "onehotencoder", "step_name": "onehotencoder"}}]
sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)(1)_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))(1)_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))(1)_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))(1)_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))(1)_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))(1)_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))(1)_verbose	false
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_memory	null
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}]
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler)(1)_verbose	false
sklearn.pipeline.Pipeline(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)(1)_memory	null
sklearn.pipeline.Pipeline(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)(1)_steps	[{"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(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)(1)_verbose	false