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Task 167132 (Supervised Classification) Speech Uploaded 15-03-2018 by Maarten van Asseldonk
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Flow

sklearn.ensemble.voting_classifier.VotingClassifier(svc=sklearn.pipeline.Pi peline(Scaler=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decompo sition.pca.PCA,Classifier=sklearn.svm.classes.SVC),kn=sklearn.neighbors.cla ssification.KNeighborsClassifier,gnb=sklearn.naive_bayes.GaussianNB,logreg= sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.Normalizer,Clas sifier=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.svm.classes.SVC(16)_C	10
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	true
sklearn.svm.classes.SVC(16)_random_state	25857
sklearn.svm.classes.SVC(16)_shrinking	true
sklearn.svm.classes.SVC(16)_tol	0.001
sklearn.svm.classes.SVC(16)_verbose	false
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	10
sklearn.neighbors.classification.KNeighborsClassifier(20)_p	2
sklearn.neighbors.classification.KNeighborsClassifier(20)_weights	"uniform"
sklearn.linear_model.logistic.LogisticRegression(10)_C	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	"l1"
sklearn.linear_model.logistic.LogisticRegression(10)_random_state	22313
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	null
sklearn.decomposition.pca.PCA(2)_random_state	45852
sklearn.decomposition.pca.PCA(2)_svd_solver	"auto"
sklearn.decomposition.pca.PCA(2)_tol	0.0
sklearn.decomposition.pca.PCA(2)_whiten	false
sklearn.naive_bayes.GaussianNB(7)_priors	null
sklearn.preprocessing.data.Normalizer(1)_copy	true
sklearn.preprocessing.data.Normalizer(1)_norm	"l2"
sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,Classifier=sklearn.svm.classes.SVC)(1)_memory	null
sklearn.ensemble.voting_classifier.VotingClassifier(svc=sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,Classifier=sklearn.svm.classes.SVC),kn=sklearn.neighbors.classification.KNeighborsClassifier,gnb=sklearn.naive_bayes.GaussianNB,logreg=sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.Normalizer,Classifier=sklearn.linear_model.logistic.LogisticRegression))(1)_flatten_transform	null
sklearn.ensemble.voting_classifier.VotingClassifier(svc=sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,Classifier=sklearn.svm.classes.SVC),kn=sklearn.neighbors.classification.KNeighborsClassifier,gnb=sklearn.naive_bayes.GaussianNB,logreg=sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.Normalizer,Classifier=sklearn.linear_model.logistic.LogisticRegression))(1)_n_jobs	-1
sklearn.ensemble.voting_classifier.VotingClassifier(svc=sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,Classifier=sklearn.svm.classes.SVC),kn=sklearn.neighbors.classification.KNeighborsClassifier,gnb=sklearn.naive_bayes.GaussianNB,logreg=sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.Normalizer,Classifier=sklearn.linear_model.logistic.LogisticRegression))(1)_voting	"soft"
sklearn.ensemble.voting_classifier.VotingClassifier(svc=sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,Classifier=sklearn.svm.classes.SVC),kn=sklearn.neighbors.classification.KNeighborsClassifier,gnb=sklearn.naive_bayes.GaussianNB,logreg=sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.Normalizer,Classifier=sklearn.linear_model.logistic.LogisticRegression))(1)_weights	[2, 1, 1, 1]
sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.Normalizer,Classifier=sklearn.linear_model.logistic.LogisticRegression)(1)_memory	null