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Task 167132 (Supervised Classification) Speech Uploaded 12-03-2018 by Nathan Cassee
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sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.pipeline.Pip eline(scaler=sklearn.preprocessing.data.StandardScaler,pca=sklearn.decompos ition.pca.PCA,reg=sklearn.linear_model.logistic.LogisticRegression))(1)	Automatically created scikit-learn flow.
sklearn.preprocessing.data.StandardScaler(5)_copy	true
sklearn.preprocessing.data.StandardScaler(5)_with_mean	true
sklearn.preprocessing.data.StandardScaler(5)_with_std	true
sklearn.linear_model.logistic.LogisticRegression(10)_C	0.07743
sklearn.linear_model.logistic.LogisticRegression(10)_class_weight	null
sklearn.linear_model.logistic.LogisticRegression(10)_dual	false
sklearn.linear_model.logistic.LogisticRegression(10)_fit_intercept	true
sklearn.linear_model.logistic.LogisticRegression(10)_intercept_scaling	1
sklearn.linear_model.logistic.LogisticRegression(10)_max_iter	100
sklearn.linear_model.logistic.LogisticRegression(10)_multi_class	"ovr"
sklearn.linear_model.logistic.LogisticRegression(10)_n_jobs	-1
sklearn.linear_model.logistic.LogisticRegression(10)_penalty	"l2"
sklearn.linear_model.logistic.LogisticRegression(10)_random_state	37016
sklearn.linear_model.logistic.LogisticRegression(10)_solver	"newton-cg"
sklearn.linear_model.logistic.LogisticRegression(10)_tol	0.0001
sklearn.linear_model.logistic.LogisticRegression(10)_verbose	0
sklearn.linear_model.logistic.LogisticRegression(10)_warm_start	false
sklearn.decomposition.pca.PCA(2)_copy	true
sklearn.decomposition.pca.PCA(2)_iterated_power	"auto"
sklearn.decomposition.pca.PCA(2)_n_components	4
sklearn.decomposition.pca.PCA(2)_random_state	20722
sklearn.decomposition.pca.PCA(2)_svd_solver	"auto"
sklearn.decomposition.pca.PCA(2)_tol	0.0
sklearn.decomposition.pca.PCA(2)_whiten	false
sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler,pca=sklearn.decomposition.pca.PCA,reg=sklearn.linear_model.logistic.LogisticRegression)(1)_memory	null
sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler,pca=sklearn.decomposition.pca.PCA,reg=sklearn.linear_model.logistic.LogisticRegression))(1)_flatten_transform	null
sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler,pca=sklearn.decomposition.pca.PCA,reg=sklearn.linear_model.logistic.LogisticRegression))(1)_n_jobs	-1
sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler,pca=sklearn.decomposition.pca.PCA,reg=sklearn.linear_model.logistic.LogisticRegression))(1)_voting	"soft"
sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler,pca=sklearn.decomposition.pca.PCA,reg=sklearn.linear_model.logistic.LogisticRegression))(1)_weights	null