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Task 167132 (Supervised Classification) Speech Uploaded 14-03-2018 by Nick Braat
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sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pip eline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classe s.SVC))(1)	Automatically created scikit-learn flow.
sklearn.svm.classes.SVC(16)_C	100
sklearn.svm.classes.SVC(16)_cache_size	200
sklearn.svm.classes.SVC(16)_class_weight	null
sklearn.svm.classes.SVC(16)_coef0	0.0
sklearn.svm.classes.SVC(16)_decision_function_shape	"ovr"
sklearn.svm.classes.SVC(16)_degree	3
sklearn.svm.classes.SVC(16)_gamma	"auto"
sklearn.svm.classes.SVC(16)_kernel	"rbf"
sklearn.svm.classes.SVC(16)_max_iter	-1
sklearn.svm.classes.SVC(16)_probability	false
sklearn.svm.classes.SVC(16)_random_state	45364
sklearn.svm.classes.SVC(16)_shrinking	true
sklearn.svm.classes.SVC(16)_tol	0.001
sklearn.svm.classes.SVC(16)_verbose	false
sklearn.preprocessing.data.MinMaxScaler(3)_copy	true
sklearn.preprocessing.data.MinMaxScaler(3)_feature_range	[0, 1]
sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC)(1)_memory	null
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_cv	5
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_error_score	"raise"
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_fit_params	null
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_iid	true
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_n_jobs	-1
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_param_grid	{"svm__C": [0.001, 0.01, 0.1, 1, 10, 100], "svm__gamma": [0.001, 0.01, 0.1, 1, 10, 100]}
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_pre_dispatch	"2*n_jobs"
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_refit	true
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_return_train_score	"warn"
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_scoring	null
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,svm=sklearn.svm.classes.SVC))(1)_verbose	0