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Task 145677 (Supervised Classification) Bioresponse Uploaded 15-03-2017 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.neighbors.classification.KNeighbo rsClassifier))(1)	Automatically created sub-component.
sklearn.neighbors.classification.KNeighborsClassifier(7)_algorithm	auto
sklearn.neighbors.classification.KNeighborsClassifier(7)_leaf_size	30
sklearn.neighbors.classification.KNeighborsClassifier(7)_metric	minkowski
sklearn.neighbors.classification.KNeighborsClassifier(7)_metric_params	None
sklearn.neighbors.classification.KNeighborsClassifier(7)_n_jobs	1
sklearn.neighbors.classification.KNeighborsClassifier(7)_n_neighbors	5
sklearn.neighbors.classification.KNeighborsClassifier(7)_p	2
sklearn.neighbors.classification.KNeighborsClassifier(7)_weights	uniform
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.neighbors.classification.KNeighborsClassifier))(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.neighbors.classification.KNeighborsClassifier))(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.neighbors.classification.KNeighborsClassifier))(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', KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=5, p=2, weights='uniform'))])
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.neighbors.classification.KNeighborsClassifier))(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.neighbors.classification.KNeighborsClassifier))(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.neighbors.classification.KNeighborsClassifier))(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.neighbors.classification.KNeighborsClassifier))(1)_param_grid	{'Classifier__n_neighbors': [1, 3, 5, 7, 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.neighbors.classification.KNeighborsClassifier))(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.neighbors.classification.KNeighborsClassifier))(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.neighbors.classification.KNeighborsClassifier))(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.neighbors.classification.KNeighborsClassifier))(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.neighbors.classification.KNeighborsClassifier))(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.neighbors.classification.KNeighborsClassifier)(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', KNeighborsClassifier(algorithm='auto', leaf_size=30, metric='minkowski', metric_params=None, n_jobs=1, n_neighbors=5, p=2, weights='uniform'))]