Run 2087078

Task 37 (Supervised Classification) diabetes Uploaded 24-04-2017 by Jeroen van Hoof
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Flow

sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.Standar dScaler,votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifie r(DecisionTreeClassifier=sklearn.tree.tree.DecisionTreeClassifier,ExtraTree Classifier=sklearn.tree.tree.ExtraTreeClassifier))(1)	Automatically created scikit-learn flow.
sklearn.tree.tree.DecisionTreeClassifier(6)_class_weight	None
sklearn.tree.tree.DecisionTreeClassifier(6)_criterion	gini
sklearn.tree.tree.DecisionTreeClassifier(6)_max_depth	None
sklearn.tree.tree.DecisionTreeClassifier(6)_max_features	None
sklearn.tree.tree.DecisionTreeClassifier(6)_max_leaf_nodes	None
sklearn.tree.tree.DecisionTreeClassifier(6)_min_impurity_split	1e-07
sklearn.tree.tree.DecisionTreeClassifier(6)_min_samples_leaf	1
sklearn.tree.tree.DecisionTreeClassifier(6)_min_samples_split	2
sklearn.tree.tree.DecisionTreeClassifier(6)_min_weight_fraction_leaf	0.0
sklearn.tree.tree.DecisionTreeClassifier(6)_presort	False
sklearn.tree.tree.DecisionTreeClassifier(6)_random_state	None
sklearn.tree.tree.DecisionTreeClassifier(6)_splitter	best
sklearn.tree.tree.ExtraTreeClassifier(1)_class_weight	None
sklearn.tree.tree.ExtraTreeClassifier(1)_criterion	gini
sklearn.tree.tree.ExtraTreeClassifier(1)_max_depth	None
sklearn.tree.tree.ExtraTreeClassifier(1)_max_features	auto
sklearn.tree.tree.ExtraTreeClassifier(1)_max_leaf_nodes	None
sklearn.tree.tree.ExtraTreeClassifier(1)_min_impurity_split	1e-07
sklearn.tree.tree.ExtraTreeClassifier(1)_min_samples_leaf	1
sklearn.tree.tree.ExtraTreeClassifier(1)_min_samples_split	2
sklearn.tree.tree.ExtraTreeClassifier(1)_min_weight_fraction_leaf	0.0
sklearn.tree.tree.ExtraTreeClassifier(1)_random_state	None
sklearn.tree.tree.ExtraTreeClassifier(1)_splitter	random
sklearn.preprocessing.data.StandardScaler(1)_copy	True
sklearn.preprocessing.data.StandardScaler(1)_with_mean	True
sklearn.preprocessing.data.StandardScaler(1)_with_std	True
sklearn.ensemble.voting_classifier.VotingClassifier(DecisionTreeClassifier=sklearn.tree.tree.DecisionTreeClassifier,ExtraTreeClassifier=sklearn.tree.tree.ExtraTreeClassifier)(1)_estimators	[('DecisionTreeClassifier', DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None, max_features=None, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, presort=False, random_state=None, splitter='best')), ('ExtraTreeClassifier', ExtraTreeClassifier(class_weight=None, criterion='gini', max_depth=None, max_features='auto', max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, random_state=None, splitter='random'))]
sklearn.ensemble.voting_classifier.VotingClassifier(DecisionTreeClassifier=sklearn.tree.tree.DecisionTreeClassifier,ExtraTreeClassifier=sklearn.tree.tree.ExtraTreeClassifier)(1)_n_jobs	1
sklearn.ensemble.voting_classifier.VotingClassifier(DecisionTreeClassifier=sklearn.tree.tree.DecisionTreeClassifier,ExtraTreeClassifier=sklearn.tree.tree.ExtraTreeClassifier)(1)_voting	soft
sklearn.ensemble.voting_classifier.VotingClassifier(DecisionTreeClassifier=sklearn.tree.tree.DecisionTreeClassifier,ExtraTreeClassifier=sklearn.tree.tree.ExtraTreeClassifier)(1)_weights	None
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifier(DecisionTreeClassifier=sklearn.tree.tree.DecisionTreeClassifier,ExtraTreeClassifier=sklearn.tree.tree.ExtraTreeClassifier))(1)_steps	[('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('votingclassifier', VotingClassifier(estimators=[('DecisionTreeClassifier', DecisionTreeClassifier(class_weight=None, criterion='gini', max_depth=None, max_features=None, max_leaf_nodes=None, min_impurity_split=1e-07, min_samples_leaf=1, min_samples_split=2, min_weight_fraction_leaf=0.0, ...min_samples_split=2, min_weight_fraction_leaf=0.0, random_state=None, splitter='random'))], n_jobs=1, voting='soft', weights=None))]