Run 1954626

Task 49 (Supervised Classification) tic-tac-toe Uploaded 03-04-2017 by Jeroen van Hoof
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Issue	#Downvotes for this reason	By

Flow

sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,polyn omialfeatures=sklearn.preprocessing.data.PolynomialFeatures,standardscaler= sklearn.preprocessing.data.StandardScaler,pca=sklearn.decomposition.pca.PCA ,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)	Automatically created scikit-learn flow.
sklearn.ensemble.forest.RandomForestClassifier(16)_bootstrap	True
sklearn.ensemble.forest.RandomForestClassifier(16)_class_weight	None
sklearn.ensemble.forest.RandomForestClassifier(16)_criterion	gini
sklearn.ensemble.forest.RandomForestClassifier(16)_max_depth	None
sklearn.ensemble.forest.RandomForestClassifier(16)_max_features	auto
sklearn.ensemble.forest.RandomForestClassifier(16)_max_leaf_nodes	None
sklearn.ensemble.forest.RandomForestClassifier(16)_min_impurity_split	1e-07
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_leaf	1
sklearn.ensemble.forest.RandomForestClassifier(16)_min_samples_split	2
sklearn.ensemble.forest.RandomForestClassifier(16)_min_weight_fraction_leaf	0.0
sklearn.ensemble.forest.RandomForestClassifier(16)_n_estimators	500
sklearn.ensemble.forest.RandomForestClassifier(16)_n_jobs	-1
sklearn.ensemble.forest.RandomForestClassifier(16)_oob_score	False
sklearn.ensemble.forest.RandomForestClassifier(16)_random_state	None
sklearn.ensemble.forest.RandomForestClassifier(16)_verbose	0
sklearn.ensemble.forest.RandomForestClassifier(16)_warm_start	False
sklearn.preprocessing.data.StandardScaler(1)_copy	True
sklearn.preprocessing.data.StandardScaler(1)_with_mean	True
sklearn.preprocessing.data.StandardScaler(1)_with_std	True
sklearn.decomposition.pca.PCA(1)_copy	True
sklearn.decomposition.pca.PCA(1)_iterated_power	auto
sklearn.decomposition.pca.PCA(1)_n_components	None
sklearn.decomposition.pca.PCA(1)_random_state	None
sklearn.decomposition.pca.PCA(1)_svd_solver	auto
sklearn.decomposition.pca.PCA(1)_tol	0.0
sklearn.decomposition.pca.PCA(1)_whiten	False
sklearn.preprocessing.data.PolynomialFeatures(1)_degree	2
sklearn.preprocessing.data.PolynomialFeatures(1)_include_bias	True
sklearn.preprocessing.data.PolynomialFeatures(1)_interaction_only	False
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,polynomialfeatures=sklearn.preprocessing.data.PolynomialFeatures,standardscaler=sklearn.preprocessing.data.StandardScaler,pca=sklearn.decomposition.pca.PCA,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)_steps	[('dualimputer', ), ('polynomialfeatures', PolynomialFeatures(degree=2, include_bias=True, interaction_only=False)), ('standardscaler', StandardScaler(copy=True, with_mean=True, with_std=True)), ('pca', PCA(copy=True, iterated_power='auto', n_components=None, random_state=None, svd_solver='auto', tol=0.0, whiten=False)), ('randomforestclassifier', RandomForestClassifier(bootstrap=True, 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, n_estimators=500, n_jobs=-1, oob_score=False, random_state=None, verbose=0, warm_start=False))]