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sklearn.naive_bayes.GaussianNB (2)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(Imputer=openml.utils.preprocessing.ConditionalImputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,VarianceThreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,Estimator=sklearn.naive_bayes.GaussianNB) (1)
Automatically created scikit-learn flow.
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openml.utils.preprocessing.ConditionalImputer (1)
Automatically created scikit-learn flow.
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sklearn.preprocessing.data.OneHotEncoder (4)
Automatically created scikit-learn flow.
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sklearn.feature_selection.variance_threshold.VarianceThreshold (1)
Automatically created scikit-learn flow.
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mlr.classif.develpartykit.ctree (10)
Learner mlr.classif.develpartykit.ctree from package(s) partykit.
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sklearn.pipeline.Pipeline(feature_select=sklearn.feature_selection.univariate_selection.SelectPercentile,classifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.feature_selection.univariate_selection.SelectPercentile (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(classifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(feature_select=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.RandomForestClassifier),classifier=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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mlr.classif.ctree (11)
Learner mlr.classif.ctree from package(s) party.
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sklearn.pipeline.Pipeline(steps__scaling=sklearn.preprocessing.data.StandardScaler,steps__selector=sklearn.feature_selection.univariate_selection.GenericUnivariateSelect,steps__classifier=sklearn.svm.classes.SVC) (1)
Automatically created sub-component.
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sklearn.preprocessing.data.StandardScaler (1)
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sklearn.feature_selection.univariate_selection.GenericUnivariateSelect (1)
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sklearn.pipeline.Pipeline(scaling=sklearn.preprocessing.data.StandardScaler,selector=sklearn.feature_selection.univariate_selection.GenericUnivariateSelect,classifier=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(scaling=sklearn.preprocessing.data.StandardScaler,selector=sklearn.feature_selection.univariate_selection.GenericUnivariateSelect,classifier=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
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mlr.regr.develpartykit.cforest (5)
Learner mlr.regr.develpartykit.cforest from package(s) partykit.
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flows.AutoSklearnFLow.AutoSklearnFlow (2)
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flows.AutoSklearnFLow.AutoSklearnFlow(preprocessor=sklearn.pipeline.Pipeline(steps__imputer=sklearn.preprocessing.imputation.Imputer,steps__onehotencoder=sklearn.preprocessing.data.OneHotEncoder,steps__variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold)) (1)
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sklearn.pipeline.Pipeline(steps__imputer=sklearn.preprocessing.imputation.Imputer,steps__onehotencoder=sklearn.preprocessing.data.OneHotEncoder,steps__variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold) (1)
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sklearn.feature_selection.variance_threshold.VarianceThreshold (2)
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mlr.classif.develpartykit.cforest (6)
Learner mlr.classif.develpartykit.cforest from package(s) partykit.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators__rf=sklearn.ensemble.forest.RandomForestClassifier,estimators__et=sklearn.ensemble.forest.ExtraTreesClassifier,estimators__gb=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (1)
Automatically created sub-component.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators__clf1=sklearn.ensemble.forest.RandomForestClassifier,estimators__clf2=sklearn.ensemble.forest.ExtraTreesClassifier,estimators__clf3=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (1)
Automatically created sub-component.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators__clf1=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created sub-component.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators__random_state=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created sub-component.
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sklearn.ensemble.voting_classifier.VotingClassifier(clf1=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=sklearn.ensemble.forest.ExtraTreesClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.voting_classifier.VotingClassifier(rf=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=sklearn.ensemble.forest.ExtraTreesClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=sklearn.ensemble.forest.ExtraTreesClassifier,weights=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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mlr.classif.rpart (30)
Learner mlr.classif.rpart from package(s) rpart.
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mlr.classif.rpart.imputed.filtered (4)
Learner mlr.classif.rpart.imputed.filtered from package(s) rpart.
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mlr.classif.rpart.tuned (6)
Learner mlr.classif.rpart.tuned from package(s) rpart.
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mlr.classif.rpart.imputed.filtered (5)
Learner mlr.classif.rpart.imputed.filtered from package(s) rpart.
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mlr.classif.rpart.tuned (7)
Learner mlr.classif.rpart.tuned from package(s) rpart.
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mlr.classif.featureless (1)
Learner mlr.classif.featureless from package(s) mlr.
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mlr.classif.randomForest (25)
Learner mlr.classif.randomForest from package(s) randomForest.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=xgboost.sklearn.XGBClassifier,weights=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.RandomForestClassifier,voting=xgboost.sklearn.XGBClassifier,weights=sklearn.ensemble.forest.ExtraTreesClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(steps__imputer=sklearn.preprocessing.imputation.Imputer,steps__onehotencoder=sklearn.preprocessing.data.OneHotEncoder,steps__variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,steps__deepforest=DeepForest.DeepForest) (1)
Automatically created sub-component.
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DeepForest.DeepForest (1)
Automatically created sub-component.
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DeepForest.DeepForest(preprocessor=sklearn.pipeline.Pipeline(steps__imputer=sklearn.preprocessing.imputation.Imputer,steps__onehotencoder=sklearn.preprocessing.data.OneHotEncoder,steps__variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold)) (1)
Automatically created sub-component.
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mlr.classif.C50.preproc (80)
Learner mlr.classif.C50.preproc from package(s) C50.
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mlr.classif.ctree.preproc (2)
Learner mlr.classif.ctree.preproc from package(s) party.
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mlr.classif.cforest.preproc (3)
Learner mlr.classif.cforest.preproc from package(s) party.
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mlr.classif.cvglmnet.preproc (2)
Learner mlr.classif.cvglmnet.preproc from package(s) glmnet.
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mlr.classif.earth.preproc (1)
Learner mlr.classif.earth.preproc from package(s) !earth.
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mlr.classif.featureless.preproc (2)
Learner mlr.classif.featureless.preproc from package(s) mlr.
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mlr.classif.evtree.preproc (2)
Learner mlr.classif.evtree.preproc from package(s) evtree.
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mlr.classif.gbm.preproc (4)
Learner mlr.classif.gbm.preproc from package(s) gbm.
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mlr.classif.glmnet.preproc (3)
Learner mlr.classif.glmnet.preproc from package(s) glmnet.
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mlr.classif.kknn.preproc (7)
Learner mlr.classif.kknn.preproc from package(s) !kknn.
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mlr.classif.ksvm.preproc (3)
Learner mlr.classif.ksvm.preproc from package(s) kernlab.
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mlr.classif.gausspr.preproc (2)
Learner mlr.classif.gausspr.preproc from package(s) kernlab.
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mlr.classif.lda.preproc (2)
Learner mlr.classif.lda.preproc from package(s) MASS.
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mlr.classif.multinom.preproc (2)
Learner mlr.classif.multinom.preproc from package(s) nnet.
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mlr.classif.mda.preproc (1)
Learner mlr.classif.mda.preproc from package(s) !mda.
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mlr.classif.naiveBayes.preproc (10)
Learner mlr.classif.naiveBayes.preproc from package(s) e1071.
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mlr.classif.nnet.preproc (4)
Learner mlr.classif.nnet.preproc from package(s) nnet.
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mlr.classif.randomForest.preproc (5)
Learner mlr.classif.randomForest.preproc from package(s) randomForest.
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mlr.classif.randomForestSRC.preproc (2)
Learner mlr.classif.randomForestSRC.preproc from package(s) randomForestSRC.
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mlr.classif.rpart.preproc (20)
Learner mlr.classif.rpart.preproc from package(s) rpart.
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mlr.classif.rda.preproc (2)
Learner mlr.classif.rda.preproc from package(s) klaR.
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mlr.classif.RRF.preproc (2)
Learner mlr.classif.RRF.preproc from package(s) RRF.
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mlr.classif.svm.preproc (4)
Learner mlr.classif.svm.preproc from package(s) e1071.
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mlr.classif.qda.preproc (3)
Learner mlr.classif.qda.preproc from package(s) MASS.
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sklearn.pipeline.Pipeline(steps__scaling=sklearn.preprocessing.data.StandardScaler,steps__classifier=sklearn.ensemble.voting_classifier.VotingClassifier(estimators__extra=sklearn.ensemble.forest.ExtraTreesClassifier,estimators__rf=sklearn.ensemble.forest.RandomForestClassifier,estimators__gradboost=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,estimators__xgboost=xgboost.sklearn.XGBClassifier)) (1)
Automatically created sub-component.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators__extra=sklearn.ensemble.forest.ExtraTreesClassifier,estimators__rf=sklearn.ensemble.forest.RandomForestClassifier,estimators__gradboost=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,estimators__xgboost=xgboost.sklearn.XGBClassifier) (1)
Automatically created sub-component.
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sklearn.pipeline.Pipeline(steps__standardscaler=sklearn.preprocessing.data.StandardScaler,steps__votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifier(estimators__extra=sklearn.ensemble.forest.ExtraTreesClassifier,estimators__rf=sklearn.ensemble.forest.RandomForestClassifier,estimators__gradboost=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,estimators__xgboost=xgboost.sklearn.XGBClassifier)) (1)
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sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifier(extra=sklearn.ensemble.forest.ExtraTreesClassifier,rf=sklearn.ensemble.forest.RandomForestClassifier,gradboost=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,xgboost=xgboost.sklearn.XGBClassifier)) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.voting_classifier.VotingClassifier(extra=sklearn.ensemble.forest.ExtraTreesClassifier,rf=sklearn.ensemble.forest.RandomForestClassifier,gradboost=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,xgboost=xgboost.sklearn.XGBClassifier) (1)
Automatically created scikit-learn flow.
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mlr.classif.xgboost (3)
Learner mlr.classif.xgboost from package(s) xgboost.
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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)
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sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier) (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)
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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)
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sklearn.pipeline.Pipeline(steps__Imputer=sklearn.preprocessing.imputation.Imputer,steps__Classifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
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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)
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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)
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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.
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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.
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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.
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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.
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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.
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sklearn.feature_selection.univariate_selection.SelectKBest (1)
Automatically created scikit-learn flow.
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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.
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sklearn.preprocessing.data.MinMaxScaler (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.voting_classifier.VotingClassifier(extra=sklearn.ensemble.forest.ExtraTreesClassifier,rf=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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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.
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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.
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sklearn.ensemble.voting_classifier.VotingClassifier(rf=sklearn.ensemble.forest.RandomForestClassifier,et=sklearn.ensemble.forest.ExtraTreesClassifier,gb=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (1)
Automatically created sub-component.
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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.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.ExtraTreesClassifier,voting=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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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.
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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.
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sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.ExtraTreesClassifier,voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=xgboost.sklearn.XGBClassifier)) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.ExtraTreesClassifier,voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=xgboost.sklearn.XGBClassifier) (1)
Automatically created scikit-learn flow.
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