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Task 12 (Supervised Classification) mfeat-factors Uploaded 03-12-2019 by Heinrich Peters
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Flow

sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer, standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.cl asses.SVC)(1)	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	"median"
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	0.05577533052194334
sklearn.svm.classes.SVC(31)_cache_size	200
sklearn.svm.classes.SVC(31)_class_weight	null
sklearn.svm.classes.SVC(31)_coef0	-0.34023879996621864
sklearn.svm.classes.SVC(31)_decision_function_shape	"ovr"
sklearn.svm.classes.SVC(31)_degree	1
sklearn.svm.classes.SVC(31)_gamma	0.0758062246427197
sklearn.svm.classes.SVC(31)_kernel	"poly"
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.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_memory	null
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_steps	[{"oml-python:serialized_object": "component_reference", "value": {"key": "simpleimputer", "step_name": "simpleimputer"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "standardscaler", "step_name": "standardscaler"}}, {"oml-python:serialized_object": "component_reference", "value": {"key": "svc", "step_name": "svc"}}]
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)_verbose	false