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sklearn.pipeline.Pipeline(SCL=sklearn.preprocessing.data.StandardScaler,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,SCL=sklearn.preprocessing.data.StandardScaler,NYS=sklearn.kernel_approximation.Nystroem,LSV=sklearn.svm.classes.LinearSVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SCL=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,SCL=sklearn.preprocessing.data.StandardScaler,LSV=sklearn.svm.classes.LinearSVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,SCL=sklearn.preprocessing.data.StandardScaler,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PLY=sklearn.preprocessing.data.PolynomialFeatures,MMS=sklearn.preprocessing.data.MinMaxScaler,PCA=sklearn.decomposition.pca.PCA,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(PLY=sklearn.preprocessing.data.PolynomialFeatures,SCL=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PLY=sklearn.preprocessing.data.PolynomialFeatures,PCA=sklearn.decomposition.pca.PCA,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PLY=sklearn.preprocessing.data.PolynomialFeatures,SCL=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PLY=sklearn.preprocessing.data.PolynomialFeatures,MAS=sklearn.preprocessing.data.MaxAbsScaler,PCA=sklearn.decomposition.pca.PCA,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PLY=sklearn.preprocessing.data.PolynomialFeatures,MAS=sklearn.preprocessing.data.MaxAbsScaler,NYS=sklearn.kernel_approximation.Nystroem,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PLY=sklearn.preprocessing.data.PolynomialFeatures,MMS=sklearn.preprocessing.data.MinMaxScaler,PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(MAS=sklearn.preprocessing.data.MaxAbsScaler,PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(MMS=sklearn.preprocessing.data.MinMaxScaler,PCA=sklearn.decomposition.pca.PCA,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,RBS=sklearn.preprocessing.data.RobustScaler,PCA=sklearn.decomposition.pca.PCA,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,MMS=sklearn.preprocessing.data.MinMaxScaler,PCA=sklearn.decomposition.pca.PCA,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,Classifier=KerasLogResClassifier.KerasLogResClassifier) (2)
Automatically created scikit-learn flow.
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sklearn.preprocessing.data.StandardScaler (23)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(NOR=sklearn.preprocessing.data.Normalizer,RBF=sklearn.kernel_approximation.RBFSampler,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,MMS=sklearn.preprocessing.data.MinMaxScaler,RBF=sklearn.kernel_approximation.RBFSampler,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(PLY=sklearn.preprocessing.data.PolynomialFeatures,NOR=sklearn.preprocessing.data.Normalizer,RBF=sklearn.kernel_approximation.RBFSampler,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(NOR=sklearn.preprocessing.data.Normalizer,PCA=sklearn.decomposition.pca.PCA,RBF=sklearn.kernel_approximation.RBFSampler,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(MMS=sklearn.preprocessing.data.MinMaxScaler,NYS=sklearn.kernel_approximation.Nystroem,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(RBS=sklearn.preprocessing.data.RobustScaler,FIC=sklearn.decomposition.fastica_.FastICA,LSV=sklearn.svm.classes.LinearSVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(PLY=sklearn.preprocessing.data.PolynomialFeatures,MMS=sklearn.preprocessing.data.MinMaxScaler,NYS=sklearn.kernel_approximation.Nystroem,LSV=sklearn.svm.classes.LinearSVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(PLY=sklearn.preprocessing.data.PolynomialFeatures,MMS=sklearn.preprocessing.data.MinMaxScaler,FIC=sklearn.decomposition.fastica_.FastICA,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SCL=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SCL=sklearn.preprocessing.data.StandardScaler,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SCL=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,MMS=sklearn.preprocessing.data.MinMaxScaler,PCA=sklearn.decomposition.pca.PCA,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,MAS=sklearn.preprocessing.data.MaxAbsScaler,PCA=sklearn.decomposition.pca.PCA,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,MAS=sklearn.preprocessing.data.MaxAbsScaler,SPC=sklearn.feature_selection.univariate_selection.SelectPercentile,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PLY=sklearn.preprocessing.data.PolynomialFeatures,BXC=sklearn.preprocessing.data.PowerTransformer,FAG=sklearn.cluster.hierarchical.FeatureAgglomeration,GNB=sklearn.naive_bayes.GaussianNB) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PLY=sklearn.preprocessing.data.PolynomialFeatures,BXC=sklearn.preprocessing.data.PowerTransformer,FAG=sklearn.cluster.hierarchical.FeatureAgglomeration,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PLY=sklearn.preprocessing.data.PolynomialFeatures,BXC=sklearn.preprocessing.data.PowerTransformer,FAG=sklearn.cluster.hierarchical.FeatureAgglomeration,RBF=sklearn.kernel_approximation.RBFSampler,LSV=sklearn.svm.classes.LinearSVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,BXC=sklearn.preprocessing.data.PowerTransformer,FAG=sklearn.cluster.hierarchical.FeatureAgglomeration,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,NYS=sklearn.kernel_approximation.Nystroem,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PLY=sklearn.preprocessing.data.PolynomialFeatures,RBS=sklearn.preprocessing.data.RobustScaler,PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(RBS=sklearn.preprocessing.data.RobustScaler,PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,LSV=sklearn.svm.classes.LinearSVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,RBS=sklearn.preprocessing.data.RobustScaler,PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,YJH=sklearn.preprocessing.data.PowerTransformer,NYS=sklearn.kernel_approximation.Nystroem,LSV=sklearn.svm.classes.LinearSVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,LSV=sklearn.svm.classes.LinearSVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(NOR=sklearn.preprocessing.data.Normalizer,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(YJH=sklearn.preprocessing.data.PowerTransformer,NYS=sklearn.kernel_approximation.Nystroem,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,MAS=sklearn.preprocessing.data.MaxAbsScaler,CART=sklearn.tree.tree.DecisionTreeClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,SCL=sklearn.preprocessing.data.StandardScaler,CART=sklearn.tree.tree.DecisionTreeClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(PLY=sklearn.preprocessing.data.PolynomialFeatures,NOR=sklearn.preprocessing.data.Normalizer,PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,KNN=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(NOR=sklearn.preprocessing.data.Normalizer,NYS=sklearn.kernel_approximation.Nystroem,KNN=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(PLY=sklearn.preprocessing.data.PolynomialFeatures,MMS=sklearn.preprocessing.data.MinMaxScaler,PCA=sklearn.decomposition.pca.PCA,NYS=sklearn.kernel_approximation.Nystroem,LSV=sklearn.svm.classes.LinearSVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SCL=sklearn.preprocessing.data.StandardScaler,NYS=sklearn.kernel_approximation.Nystroem,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(PLY=sklearn.preprocessing.data.PolynomialFeatures,MMS=sklearn.preprocessing.data.MinMaxScaler,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(MMS=sklearn.preprocessing.data.MinMaxScaler,NYS=sklearn.kernel_approximation.Nystroem,LGR=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,RBS=sklearn.preprocessing.data.RobustScaler,EXT=sklearn.tree.tree.ExtraTreeClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(PLY=sklearn.preprocessing.data.PolynomialFeatures,SCL=sklearn.preprocessing.data.StandardScaler,RF=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.discriminant_analysis.QuadraticDiscriminantAnalysis (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.forest.ExtraTreesClassifier (11)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(PLY=sklearn.preprocessing.data.PolynomialFeatures,SCL=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(SMP=sklearn.impute.SimpleImputer,MMS=sklearn.preprocessing.data.MinMaxScaler,PCA=sklearn.decomposition.pca.PCA,LDA=sklearn.discriminant_analysis.LinearDiscriminantAnalysis) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,Classifier=KerasLogResClassifier.KerasLogResClassifier) (3)
Automatically created scikit-learn flow.
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sklearn.preprocessing.data.StandardScaler (24)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(preprocessing=sklearn.compose._column_transformer.ColumnTransformer(imputer=sklearn.impute.SimpleImputer,cat_encoder=category_encoders.target_encoder.TargetEncoder),algorithm=sklearn.ensemble.forest.RandomForestClassifier) (2)
Automatically created scikit-learn flow.
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sklearn.compose._column_transformer.ColumnTransformer(imputer=sklearn.impute.SimpleImputer,cat_encoder=category_encoders.target_encoder.TargetEncoder) (3)
Automatically created scikit-learn flow.
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sklearn.impute.SimpleImputer (9)
Automatically created scikit-learn flow.
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sklearn.ensemble.forest.RandomForestClassifier (50)
Automatically created scikit-learn flow.
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sklearn.preprocessing._encoders.OrdinalEncoder (1)
Automatically created scikit-learn flow.
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sklearn.compose._column_transformer.ColumnTransformer(imputer=sklearn.impute.SimpleImputer,basic_encoder=category_encoders.one_hot.OneHotEncoder) (1)
Automatically created scikit-learn flow.
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sklearn.impute.SimpleImputer (10)
Automatically created scikit-learn flow.
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category_encoders.one_hot.OneHotEncoder (1)
Automatically created scikit-learn flow.
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sklearn.compose._column_transformer.ColumnTransformer(num_imputer=sklearn.impute.SimpleImputer,basic_encoder=category_encoders.one_hot.OneHotEncoder) (1)
Automatically created scikit-learn flow.
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sklearn.compose._column_transformer.ColumnTransformer(non_binary_imputer=__main__.SimpleImputer2) (1)
Automatically created scikit-learn flow.
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__main__.SimpleImputer2 (1)
Automatically created scikit-learn flow.
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sklearn.compose._column_transformer.ColumnTransformer(non_binary_imputer=__main__.SklearnSimpleImputerCloneWithMedianStrategy) (1)
Automatically created scikit-learn flow.
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__main__.SklearnSimpleImputerCloneWithMedianStrategy (1)
Automatically created scikit-learn flow.
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sklearn.compose._column_transformer.ColumnTransformer(other_cat_imputer=__main__.SklearnSimpleImputerCloneWithMedianStrategy) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputation=sklearn.compose._column_transformer.ColumnTransformer(numeric_imputer=sklearn.impute.SimpleImputer,categorical_imputer=sklearn_clone.SklearnSimpleImputerCloneWithMedianStrategy),encoding=sklearn.compose._column_transformer.ColumnTransformer(basic_encoder=category_encoders.one_hot.OneHotEncoder),learner=sklearn.naive_bayes.GaussianNB) (1)
Automatically created scikit-learn flow.
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sklearn.compose._column_transformer.ColumnTransformer(numeric_imputer=sklearn.impute.SimpleImputer,categorical_imputer=sklearn_clone.SklearnSimpleImputerCloneWithMedianStrategy) (1)
Automatically created scikit-learn flow.
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sklearn_clone.SklearnSimpleImputerCloneWithMedianStrategy (1)
Automatically created scikit-learn flow.
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sklearn.compose._column_transformer.ColumnTransformer(basic_encoder=category_encoders.one_hot.OneHotEncoder) (1)
Automatically created scikit-learn flow.
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sklearn.naive_bayes.GaussianNB (13)
Automatically created scikit-learn flow.
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weka.classifiers.meta.multisearch.RandomSearch (2)
Weka implementation.
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weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree)) (2)
Weka implementation.
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weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize) (2)
Weka implementation.
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weka.filters.unsupervised.attribute.ReplaceMissingValues (2)
Weka implementation.
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weka.filters.unsupervised.attribute.RemoveUseless (2)
Weka implementation.
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weka.filters.unsupervised.attribute.Normalize (2)
Weka implementation.
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weka.classifiers.meta.LogitBoost(weka.classifiers.trees.REPTree) (2)
J. Friedman, T. Hastie, R. Tibshirani (1998). Additive Logistic Regression: a Statistical View of Boosting. Stanford University.
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weka.classifiers.trees.REPTree (2)
Weka implementation.
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sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,svc=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.feature_selection.variance_threshold.VarianceThreshold (22)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,hotencoding=sklearn.preprocessing._encoders.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.feature_selection.variance_threshold.VarianceThreshold (23)
Automatically created scikit-learn flow.
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shogun.machine.Perceptron (1)
Automatically created shogun flow.
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shogun.kernel.GaussianKernel (1)
Automatically created shogun flow.
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shogun.machine.SVM (1)
Automatically created shogun flow.
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shogun.machine.SVMLight (1)
Automatically created shogun flow.
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mlr.classif.randomForest (46)
Learner mlr.classif.randomForest from package(s) randomForest.
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sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,adaboostclassifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)) (1)
Automatically created scikit-learn flow.
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sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=sklearn.preprocessing.data.StandardScaler),nominal=sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)) (4)
Automatically created scikit-learn flow.
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