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Stanley Clark
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Stanley's flows

sklearn.pipeline.Pipeline(randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
3 runs0 likes0 downloads0 reach1 impact
sklearn.pipeline.Pipeline(minmaxscaler=sklearn.preprocessing.data.MinMaxScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,genericunivariateselect=sklearn.feature_selection.univariate_selection.GenericUnivariateSelect,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),gaussiannb=sklearn.naive_bayes.GaussianNB) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),logisticregression=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(minmaxscaler=sklearn.preprocessing.data.MinMaxScaler,selectkbest=sklearn.feature_selection.univariate_selection.SelectKBest,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing.data.MinMaxScaler (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(selectkbest=sklearn.feature_selection.univariate_selection.SelectKBest,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.feature_selection.univariate_selection.SelectKBest (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.svm.classes.LinearSVC),svc=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.svm.classes.LinearSVC),svc=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),svc=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
8 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(steps__scaling=sklearn.preprocessing.data.StandardScaler,steps__selector=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),steps__RandomForestClassifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(steps__scaling=sklearn.preprocessing.data.StandardScaler,steps__selector=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),steps__classifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created sub-component.
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sklearn.pipeline.Pipeline(steps__Imputer=sklearn.preprocessing.imputation.Imputer,steps__Classifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created sub-component.
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sklearn.pipeline.Pipeline(steps__StandardScaler=sklearn.preprocessing.data.StandardScaler,steps__SelectFromModel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),steps__RandomForestClassifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created sub-component.
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sklearn.pipeline.Pipeline(steps__StandardScaler=sklearn.preprocessing.data.StandardScaler,steps__SelectFromModel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),steps__Classifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created sub-component.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(steps__Scaling=sklearn.preprocessing.data.StandardScaler,steps__features=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),steps__Classifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created sub-component.
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sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier) (1)
Automatically created sub-component.
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