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Task 167132 (Supervised Classification) Speech Uploaded 15-03-2018 by Bhoomica Nataraja
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Flow

sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.pipeline.Pip eline(Classifier2=sklearn.linear_model.logistic.LogisticRegression),knn=skl earn.pipeline.Pipeline(Scaler1=sklearn.preprocessing.data.Normalizer,PCA1=s klearn.decomposition.pca.PCA,Classifier1=sklearn.neighbors.classification.K NeighborsClassifier))(1)	Automatically created scikit-learn flow.
sklearn.neighbors.classification.KNeighborsClassifier(20)_algorithm	"auto"
sklearn.neighbors.classification.KNeighborsClassifier(20)_leaf_size	30
sklearn.neighbors.classification.KNeighborsClassifier(20)_metric	"minkowski"
sklearn.neighbors.classification.KNeighborsClassifier(20)_metric_params	null
sklearn.neighbors.classification.KNeighborsClassifier(20)_n_jobs	1
sklearn.neighbors.classification.KNeighborsClassifier(20)_n_neighbors	30
sklearn.neighbors.classification.KNeighborsClassifier(20)_p	2
sklearn.neighbors.classification.KNeighborsClassifier(20)_weights	"uniform"
sklearn.linear_model.logistic.LogisticRegression(10)_C	0.1
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	24489
sklearn.linear_model.logistic.LogisticRegression(10)_solver	"liblinear"
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	0.99
sklearn.decomposition.pca.PCA(2)_random_state	644
sklearn.decomposition.pca.PCA(2)_svd_solver	"auto"
sklearn.decomposition.pca.PCA(2)_tol	0.0
sklearn.decomposition.pca.PCA(2)_whiten	false
sklearn.preprocessing.data.Normalizer(1)_copy	true
sklearn.preprocessing.data.Normalizer(1)_norm	"l2"
sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.pipeline.Pipeline(Classifier2=sklearn.linear_model.logistic.LogisticRegression),knn=sklearn.pipeline.Pipeline(Scaler1=sklearn.preprocessing.data.Normalizer,PCA1=sklearn.decomposition.pca.PCA,Classifier1=sklearn.neighbors.classification.KNeighborsClassifier))(1)_flatten_transform	null
sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.pipeline.Pipeline(Classifier2=sklearn.linear_model.logistic.LogisticRegression),knn=sklearn.pipeline.Pipeline(Scaler1=sklearn.preprocessing.data.Normalizer,PCA1=sklearn.decomposition.pca.PCA,Classifier1=sklearn.neighbors.classification.KNeighborsClassifier))(1)_n_jobs	1
sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.pipeline.Pipeline(Classifier2=sklearn.linear_model.logistic.LogisticRegression),knn=sklearn.pipeline.Pipeline(Scaler1=sklearn.preprocessing.data.Normalizer,PCA1=sklearn.decomposition.pca.PCA,Classifier1=sklearn.neighbors.classification.KNeighborsClassifier))(1)_voting	"soft"
sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.pipeline.Pipeline(Classifier2=sklearn.linear_model.logistic.LogisticRegression),knn=sklearn.pipeline.Pipeline(Scaler1=sklearn.preprocessing.data.Normalizer,PCA1=sklearn.decomposition.pca.PCA,Classifier1=sklearn.neighbors.classification.KNeighborsClassifier))(1)_weights	null
sklearn.pipeline.Pipeline(Classifier2=sklearn.linear_model.logistic.LogisticRegression)(1)_memory	null
sklearn.pipeline.Pipeline(Scaler1=sklearn.preprocessing.data.Normalizer,PCA1=sklearn.decomposition.pca.PCA,Classifier1=sklearn.neighbors.classification.KNeighborsClassifier)(1)_memory	null