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mlr.classif.mlp.preproc.preproc (3)
Learner mlr.classif.mlp.preproc.preproc from package(s) RSNNS.
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mlr.classif.logreg.preproc.preproc (1)
Learner mlr.classif.logreg.preproc.preproc from package(s) stats.
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mlr.classif.PART.preproc.preproc (3)
Learner mlr.classif.PART.preproc.preproc from package(s) RWeka.
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mlr.classif.randomForest.preproc.preproc (2)
Learner mlr.classif.randomForest.preproc.preproc from package(s) randomForest.
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mlr.classif.rpart (10)
Learner mlr.classif.rpart from package(s) rpart.
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mlr.classif.glmboost (2)
Learner mlr.classif.glmboost from package(s) mboost.
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mlr.regr.penalized.fusedlasso (1)
Learner mlr.regr.penalized.fusedlasso from package(s) !penalized.
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mlr.classif.rpart (13)
Learner mlr.classif.rpart from package(s) rpart.
2 runs0 likes0 downloads0 reach1 impact
sklearn.ensemble.forest.RandomForestClassifier (12)
Flow generated by run_task
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mlr.classif.rpart.tuned (2)
Learner mlr.classif.rpart.tuned from package(s) rpart.
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mlr.classif.rpart.preproc (17)
Learner mlr.classif.rpart.preproc from package(s) rpart.
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mlr.classif.rpart.bagged.preproc (2)
Learner mlr.classif.rpart.bagged.preproc from package(s) rpart.
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mlr.weightedclasses.classif.gbm.preproc (1)
Learner mlr.weightedclasses.classif.gbm.preproc from package(s) gbm.
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mlr.weightedclasses.classif.randomForestSRC (1)
Learner mlr.weightedclasses.classif.randomForestSRC from package(s) randomForestSRC.
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weka.CostSensitiveClassifier_LMT (1)
Weka implementation of CostSensitiveClassifier
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weka.CostSensitiveClassifier_HoeffdingTree (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.Bagging_J48 (8)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
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weka.FilteredClassifier_CostSensitiveClassifier_RandomTree (2)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.LibSVM (9)
Yasser EL-Manzalawy (2005). WLSVM. URL http://www.cs.iastate.edu/~yasser/wlsvm/. Chih-Chung Chang, Chih-Jen Lin (2001). LIBSVM - A Library for Support Vector Machines. URL…
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weka.CostSensitiveClassifier_VotedPerceptron (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_LogitBoost_RandomForest (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_J48 (5)
Weka implementation of CostSensitiveClassifier
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weka.CostSensitiveClassifier_Bagging_J48 (2)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_IterativeClassifierOptimizer_LogitBoost_DecisionStump (2)
Weka implementation of CostSensitiveClassifier
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weka.CostSensitiveClassifier_JRip (2)
Weka implementation of CostSensitiveClassifier
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weka.RandomCommittee_Bagging_LogitBoost_DecisionStump (1)
Weka implementation of RandomCommittee
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weka.CostSensitiveClassifier_Bagging_REPTree (4)
Weka implementation of CostSensitiveClassifier
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weka.CostSensitiveClassifier_DecisionTable (1)
Weka implementation of CostSensitiveClassifier
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weka.CostSensitiveClassifier_Bagging_SimpleLogistic (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.CostSensitiveClassifier_NaiveBayes (3)
Weka implementation of CostSensitiveClassifier
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weka.CostSensitiveClassifier_RandomSubSpace_SimpleLogistic (1)
Weka implementation of CostSensitiveClassifier
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weka.RandomSubSpace_SimpleLogistic (1)
Tin Kam Ho (1998). The Random Subspace Method for Constructing Decision Forests. IEEE Transactions on Pattern Analysis and Machine Intelligence. 20(8):832-844. URL…
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weka.CostSensitiveClassifier_Bagging_IBk (1)
Weka implementation of CostSensitiveClassifier
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weka.Vote_NaiveBayes (2)
Ludmila I. Kuncheva (2004). Combining Pattern Classifiers: Methods and Algorithms. John Wiley and Sons, Inc.. J. Kittler, M. Hatef, Robert P.W. Duin, J. Matas (1998). On combining classifiers. IEEE…
2 runs0 likes0 downloads0 reach0 impact
weka.AdaBoostM1_NaiveBayes (4)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_Bagging_LogitBoost_DecisionStump (3)
Weka implementation of CostSensitiveClassifier
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weka.CostSensitiveClassifier_Bagging_AdaBoostM1_DecisionStump (1)
Weka implementation of CostSensitiveClassifier
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__main__.Flow (1)
Flow generated by run_task
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mlr.classif.randomForest (22)
Learner mlr.classif.randomForest from package(s) randomForest.
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mlr.classif.rpart.tuned (5)
Learner mlr.classif.rpart.tuned from package(s) rpart.
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mlr.classif.randomForest (23)
Learner mlr.classif.randomForest from package(s) randomForest.
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sklearn.naive_bayes.GaussianNB (1)
Automatically created sub-component.
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mlr.classif.RRF.preproc (1)
Learner mlr.classif.RRF.preproc from package(s) RRF.
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mlr.classif.glmnet (2)
Learner mlr.classif.glmnet from package(s) glmnet.
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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.
2 runs0 likes0 downloads0 reach0 impact
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.tuned (6)
Learner mlr.classif.rpart.tuned from package(s) rpart.
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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.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.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,votingclassifier=sklearn.ensemble.voting_classifier.VotingClassifier(estimators=sklearn.ensemble.forest.ExtraTreesClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=xgboost.sklearn.XGBClassifier)) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.model_selection._search.GridSearchCV(estimator=sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,select=sklearn.feature_selection.univariate_selection.SelectPercentile,scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.svm.classes.SVC)) (1)
Automatically created sub-component.
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sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Feature_Removal=sklearn.feature_selection.univariate_selection.SelectKBest,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.ensemble.weight_boosting.AdaBoostClassifier (5)
Automatically created sub-component.
2 runs0 likes0 downloads0 reach1 impact
sklearn.ensemble.voting_classifier.VotingClassifier(voting=sklearn.ensemble.forest.RandomForestClassifier,weights=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier,n_jobs=__main__.SecondGradientBoostingClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(Imputer=openml.utils.preprocessing.ConditionalImputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,VarianceThreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,Estimator=sklearn.model_selection._search.GridSearchCV(estimator=sklearn.ensemble.forest.RandomForestClassifier)) (1)
Automatically created scikit-learn flow.
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mlr.regr.rpart (4)
Learner mlr.regr.rpart from package(s) rpart.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,polynomialfeatures=sklearn.preprocessing.data.PolynomialFeatures,pca=sklearn.decomposition.pca.PCA,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,kernelpca=sklearn.decomposition.kernel_pca.KernelPCA,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
weka.MultiSearch_J48 (5)
Weka implementation of MultiSearch
2 runs0 likes0 downloads0 reach2 impact
weka.Bagging_MultilayerPerceptron (4)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
2 runs0 likes0 downloads0 reach0 impact
weka.Stacking_ZeroR (3)
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
2 runs0 likes0 downloads0 reach1 impact
weka.OneR (21)
R.C. Holte (1993). Very simple classification rules perform well on most commonly used datasets. Machine Learning. 11:63-91.
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sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,pca=sklearn.decomposition.pca.PCA,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,svc=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
weka.Stacking_AttributeSelectedClassifier (1)
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,robustscaler=sklearn.preprocessing.data.RobustScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_MultilayerPerceptron (2)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.FilteredClassifier_J48 (2)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,variancethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),kneighborsclassifier=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,selectfrommodel=sklearn.feature_selection.from_model.SelectFromModel(estimator=sklearn.ensemble.forest.ExtraTreesClassifier),kneighborsclassifier=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_OneR (2)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,nusvc=sklearn.svm.classes.NuSVC) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,nusvc=sklearn.svm.classes.NuSVC) (1)
Automatically created scikit-learn flow.
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weka.MultiClassClassifier_SMO_PolyKernel (1)
Weka implementation of MultiClassClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.FilteredClassifier_Logistic (1)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach2 impact
weka.FilteredClassifier_Bagging_RandomForest (3)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach2 impact
weka.CostSensitiveClassifier_AttributeSelectedClassifier_NaiveBayes (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.FilteredClassifier_CostSensitiveClassifier_NaiveBayes (1)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach2 impact
sklearn.pipeline.Pipeline(DualImputer=helper.dual_imputer.DualImputer,adaboostclassifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(DualImputer=helper.dual_imputer.DualImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,standardscaler=sklearn.preprocessing.data.StandardScaler,nusvc=sklearn.svm.classes.NuSVC) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(DualImputer=helper.dual_imputer.DualImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,standardscaler=sklearn.preprocessing.data.StandardScaler,logisticregression=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_AdaBoostM1_DecisionStump (2)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.BayesNet (3)
Weka implementation of BayesNet
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weka.FilteredClassifier_FilteredClassifier_FilteredClassifier_Bagging_IBk (1)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.FilteredClassifier_FilteredClassifier_Logistic (1)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach2 impact
weka.NaiveBayesMultinomialText (1)
Weka implementation of NaiveBayesMultinomialText
2 runs0 likes0 downloads0 reach0 impact
weka.CVParameterSelection_RandomForest (1)
R. Kohavi (1995). Wrappers for Performance Enhancement and Oblivious Decision Graphs. Department of Computer Science, Stanford University.
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weka.FilteredClassifier_CostSensitiveClassifier_RandomForest (3)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach2 impact
weka.NaiveBayesUpdateable (12)
George H. John, Pat Langley: Estimating Continuous Distributions in Bayesian Classifiers. In: Eleventh Conference on Uncertainty in Artificial Intelligence, San Mateo, 338-345, 1995.
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weka.FilteredClassifier_FilteredClassifier_FilteredClassifier_CostSensitiveClassifier_SMO_PolyKernel (1)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.Bagging_REPTree (27)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_AttributeSelectedClassifier_Logistic (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.FilteredClassifier_FilteredClassifier_FilteredClassifier_Logistic (1)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_FilteredClassifier_Bagging_Logistic (1)
Weka implementation of CostSensitiveClassifier
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weka.AdaBoostM1_FilteredClassifier_RandomForest (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
2 runs0 likes0 downloads0 reach0 impact
weka.JRip (8)
William W. Cohen: Fast Effective Rule Induction. In: Twelfth International Conference on Machine Learning, 115-123, 1995.
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_RandomForest (6)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach2 impact
sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,logisticregression=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
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