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Task 145677 (Supervised Classification) Bioresponse Uploaded 13-03-2017 by Xiaolei Wang
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sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pip eline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.featu re_selection.univariate_selection.SelectPercentile,scaler=sklearn.preproces sing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)	Automatically created sub-component.
sklearn.svm.classes.SVC(5)_C	1.0
sklearn.svm.classes.SVC(5)_cache_size	200
sklearn.svm.classes.SVC(5)_class_weight	None
sklearn.svm.classes.SVC(5)_coef0	0.0
sklearn.svm.classes.SVC(5)_decision_function_shape	None
sklearn.svm.classes.SVC(5)_degree	3
sklearn.svm.classes.SVC(5)_gamma	auto
sklearn.svm.classes.SVC(5)_kernel	rbf
sklearn.svm.classes.SVC(5)_max_iter	-1
sklearn.svm.classes.SVC(5)_probability	True
sklearn.svm.classes.SVC(5)_random_state	None
sklearn.svm.classes.SVC(5)_shrinking	True
sklearn.svm.classes.SVC(5)_tol	0.001
sklearn.svm.classes.SVC(5)_verbose	False
sklearn.preprocessing.imputation.Imputer(3)_axis	0
sklearn.preprocessing.imputation.Imputer(3)_copy	True
sklearn.preprocessing.imputation.Imputer(3)_missing_values	NaN
sklearn.preprocessing.imputation.Imputer(3)_strategy	mean
sklearn.preprocessing.imputation.Imputer(3)_verbose	0
sklearn.feature_selection.univariate_selection.SelectPercentile(1)_percentile	5
sklearn.feature_selection.univariate_selection.SelectPercentile(1)_score_func
sklearn.preprocessing.data.MinMaxScaler(1)_copy	True
sklearn.preprocessing.data.MinMaxScaler(1)_feature_range	(0, 1)
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_cv	10
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_error_score	raise
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_estimator	Pipeline(steps=[('Imputer', Imputer(axis=0, copy=True, missing_values='NaN', strategy='mean', verbose=0)), ('select', SelectPercentile(percentile=5, score_func=)), ('scaler', MinMaxScaler(copy=True, feature_range=(0, 1))), ('Classifier', SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma='auto', kernel='rbf', max_iter=-1, probability=True, random_state=None, shrinking=True, tol=0.001, verbose=False))])
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_fit_params	{}
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_iid	True
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_n_jobs	-1
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_param_grid	{'Classifier__C': [0.01, 0.1, 1, 10], 'Classifier__gamma': [0.01, 0.1, 1, 10]}
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_pre_dispatch	2*n_jobs
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_refit	True
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_return_train_score	True
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_scoring	roc_auc
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC))(1)_verbose	0
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC)(1)_steps	[('Imputer', Imputer(axis=0, copy=True, missing_values='NaN', strategy='mean', verbose=0)), ('select', SelectPercentile(percentile=5, score_func=)), ('scaler', MinMaxScaler(copy=True, feature_range=(0, 1))), ('Classifier', SVC(C=1.0, cache_size=200, class_weight=None, coef0=0.0, decision_function_shape=None, degree=3, gamma='auto', kernel='rbf', max_iter=-1, probability=True, random_state=None, shrinking=True, tol=0.001, verbose=False))]