OpenML
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21339 results
weka.MDD (1)
Oded Maron (1998). Learning from ambiguity. O. Maron, T. Lozano-Perez (1998). A Framework for Multiple Instance Learning. Neural Information Processing Systems. 10.
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weka.FilteredClassifier_ReplaceMissingValues_MDD (1)
Weka implementation of FilteredClassifier
2 runs0 likes1 downloads1 reach0 impact
weka.ZeroR (11)
Weka implementation of ZeroR
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classif.randomForest (47)
Learner classif.randomForest from package(s) randomForest.
2 runs0 likes1 downloads1 reach0 impact
classif.naiveBayes.bagged (1)
Learner classif.naiveBayes.bagged from package(s) e1071.
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mlr.classif.rpart.tuned (16)
Learner mlr.classif.rpart.tuned from package(s) rpart.
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sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehot=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC) (2)
Automatically created scikit-learn flow.
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weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.RBFKernel,weka.classifiers.functions.Logistic) (2)
J. Platt: Fast Training of Support Vector Machines using Sequential Minimal Optimization. In B. Schoelkopf and C. Burges and A. Smola, editors, Advances in Kernel Methods - Support Vector Learning,…
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sklearn.tree.tree.DecisionTreeClassifier (51)
A decision tree classifier.
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sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler),cat=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder)),svc=sklearn.svm.classes.SVC) (3)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.pipeline.Pipeline(svc=sklearn.svm.classes.SVC) (4)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier) (5)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing._data.StandardScaler,classifier=sklearn.neighbors._classification.KNeighborsClassifier) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,gaussiannb=sklearn.naive_bayes.GaussianNB) (1)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
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sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=xgboost.sklearn.XGBClassifier) (3)
Pipeline of transforms with a final estimator. Sequentially apply a list of transforms and a final estimator. Intermediate steps of the pipeline must be 'transforms', that is, they must implement fit…
2 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble._forest.RandomForestClassifier (2)
A random forest classifier. A random forest is a meta estimator that fits a number of decision tree classifiers on various sub-samples of the dataset and uses averaging to improve the predictive…
2 runs0 likes0 downloads0 reach2 impact
sklearn.naive_bayes.GaussianNB (19)
Gaussian Naive Bayes (GaussianNB) Can perform online updates to model parameters via :meth:`partial_fit`. For details on algorithm used to update feature means and variance online, see Stanford CS…
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torch.nn.modules.container.Sequential.b5ab24e63b447fae (1)
Automatically created pytorch flow.
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mxnet.gluon.nn.basic_layers.HybridSequential.e59b914b (1)
Automatically created scikit-learn flow.
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sklearn.linear_model.logistic.LogisticRegression (25)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(Imputer=sklearn.impute.SimpleImputer,OneHotEncoder=sklearn.preprocessing._encoders.OneHotEncoder,fs=sklearn.feature_selection.univariate_selection.SelectPercentile,rf=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,estimator=sklearn.tree.tree.DecisionTreeClassifier) (17)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach1 impact
mlr.costsens.classif.gbm.filtered (1)
Learner mlr.costsens.classif.gbm.filtered from package(s) FSelector, gbm.
2 runs0 likes0 downloads0 reach0 impact
mlr.costsens.classif.nnet (1)
Learner mlr.costsens.classif.nnet from package(s) nnet.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute.SimpleImputer,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier) (2)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(imputer=sklearn.impute.SimpleImputer,estimator=sklearn.tree.tree.DecisionTreeClassifier) (5)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,logisticregression=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_CostSensitiveClassifier_AdaBoostM1_REPTree (1)
Weka implementation of AttributeSelectedClassifier
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weka.CostSensitiveClassifier_AdaBoostM1_REPTree (8)
Weka implementation of CostSensitiveClassifier
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weka.CostSensitiveClassifier_FilteredClassifier_AdaBoostM1_RandomForest (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_FilteredClassifier_AdaBoostM1_MultilayerPerceptron (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.CostSensitiveClassifier_AdaBoostM1_NaiveBayes (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_CostSensitiveClassifier_AdaBoostM1_DecisionStump (1)
Weka implementation of AttributeSelectedClassifier
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,kneighborsclassifier=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
weka.RandomizableFilteredClassifier_Vote_RandomizableFilteredClassifier_RandomTree (1)
Weka implementation of RandomizableFilteredClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.MultiSearch_RandomizableFilteredClassifier_BayesNet (1)
Weka implementation of MultiSearch
2 runs0 likes0 downloads0 reach0 impact
weka.MultiSearch_RandomizableFilteredClassifier_RandomizableFilteredClassifier_BayesNet (1)
Weka implementation of MultiSearch
2 runs0 likes0 downloads0 reach0 impact
weka.RandomizableFilteredClassifier_Vote_LMT (1)
Weka implementation of RandomizableFilteredClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.RandomizableFilteredClassifier_Vote_RandomForest (1)
Weka implementation of RandomizableFilteredClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.Vote_RandomizableFilteredClassifier (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…
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weka.FilteredClassifier_CostSensitiveClassifier_SimpleLogistic (2)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.CostSensitiveClassifier_Bagging_DecisionStump (2)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_AdaBoostM1_CostSensitiveClassifier_SimpleLogistic (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.Vote_RandomTree (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 reach2 impact
weka.CostSensitiveClassifier_NaiveBayes (5)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.AdaBoostM1_CostSensitiveClassifier_RandomTree (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
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weka.RandomizableFilteredClassifier_Vote_RandomizableFilteredClassifier_RandomTree (2)
Weka implementation of RandomizableFilteredClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.FilteredClassifier_CostSensitiveClassifier_RandomForest (4)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.FilteredClassifier_RandomizableFilteredClassifier_LMT (1)
Weka implementation of FilteredClassifier
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weka.RandomizableFilteredClassifier_AdaBoostM1_NaiveBayes (1)
Weka implementation of RandomizableFilteredClassifier
2 runs0 likes0 downloads0 reach0 impact
extra.neural_network.NeuralNetwork (2)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,svc=sklearn.svm.classes.SVC) (2)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (2)
Automatically created scikit-learn flow.
2 runs0 likes1 downloads1 reach0 impact
wrapper.optimus.OptimusCV (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
nl.liacs.subdisc.SubgroupDiscovery (1)
Subgroup Discovery search algorithm.
2 runs0 likes0 downloads0 reach0 impact
mlr.classif.gbm (3)
Learner mlr.classif.gbm from package(s) gbm.
2 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_LogitBoost_DecisionStump (2)
Weka implementation of AttributeSelectedClassifier
2 runs0 likes0 downloads0 reach2 impact
sklearn.svm.classes.SVC (10)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.tree.tree.DecisionTreeClassifier (11)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.bagging.BaggingClassifier(base_estimator=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.linear_model.logistic.LogisticRegression (7)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Bagging_BayesNet (1)
Weka implementation of AttributeSelectedClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_RandomCommittee_RandomForest (1)
Weka implementation of AttributeSelectedClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Vote_SMO (1)
Weka implementation of AttributeSelectedClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_Vote_SimpleLogistic (1)
Weka implementation of AttributeSelectedClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_AdaBoostM1_DecisionTable (1)
Weka implementation of AttributeSelectedClassifier
2 runs0 likes0 downloads0 reach0 impact
mlr.classif.cforest (4)
Learner mlr.classif.cforest from package(s) party.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (4)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.forest.RandomForestClassifier (23)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach2 impact
mlr.classif.randomForestSRC.imputed.preproc (1)
Learner mlr.classif.randomForestSRC.imputed.preproc from package(s) randomForestSRC.
2 runs0 likes0 downloads0 reach0 impact
__main__.PythonChallengeClassifier (2)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (6)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach1 impact
sklearn.tree.tree.ExtraTreeClassifier (4)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.svm.classes.SVC) (2)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
mlr.classif.randomForest (34)
Learner mlr.classif.randomForest from package(s) randomForest.
2 runs0 likes0 downloads0 reach0 impact
sklearn.tree.tree.ExtraTreeClassifier (8)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach2 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (10)
Automatically created scikit-learn flow.
2 runs0 likes1 downloads1 reach2 impact
sklearn.tree.tree.ExtraTreeClassifier (9)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (11)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
mlr.classif.glmnet (12)
Learner mlr.classif.glmnet from package(s) glmnet.
2 runs0 likes0 downloads0 reach0 impact
mlr.classif.kknn (15)
Learner mlr.classif.kknn from package(s) !kknn.
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mlr.classif.rpart (44)
Learner mlr.classif.rpart from package(s) rpart.
2 runs0 likes0 downloads0 reach0 impact
mlr.classif.ctree (16)
Learner mlr.classif.ctree from package(s) party.
2 runs0 likes0 downloads0 reach0 impact
sklearn.svm.classes.LinearSVC (5)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach1 impact
mlr.classif.ranger (17)
Learner mlr.classif.ranger from package(s) ranger.
2 runs0 likes0 downloads0 reach0 impact
weka.MultilayerPerceptron (10)
Weka implementation of MultilayerPerceptron
2 runs0 likes0 downloads0 reach1 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (14)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach1 impact
xgboost.sklearn.XGBClassifier (5)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,scaler=sklearn.preprocessing.data.MinMaxScaler,estimator=sklearn.svm.classes.LinearSVC) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.naive_bayes.GaussianNB (7)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach2 impact
sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.StandardScaler,pca=sklearn.decomposition.pca.PCA,reg=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(scaler=sklearn.preprocessing.data.MinMaxScaler,Classifier=sklearn.neighbors.classification.KNeighborsClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach1 impact
sklearn.pipeline.Pipeline(Scaler=sklearn.preprocessing.data.StandardScaler,PCA=sklearn.decomposition.pca.PCA,Classifier=sklearn.ensemble.voting_classifier.VotingClassifier(lr=sklearn.linear_model.logistic.LogisticRegression,knn=sklearn.neighbors.classification.KNeighborsClassifier,svc=sklearn.svm.classes.SVC)) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.Normalizer,dimension_reduction=sklearn.decomposition.pca.PCA,classifier=sklearn.svm.classes.SVC) (1)
Automatically created scikit-learn flow.
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sklearn.pipeline.Pipeline(Classifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach1 impact
sklearn.ensemble.voting_classifier.VotingClassifier(knn=sklearn.neighbors.classification.KNeighborsClassifier,svc=sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.StandardScaler,dimension_reduction=sklearn.decomposition.pca.PCA,classifier=sklearn.svm.classes.SVC),rf=sklearn.ensemble.forest.RandomForestClassifier) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.StandardScaler,dimension_reduction=sklearn.decomposition.pca.PCA,classifier=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.voting_classifier.VotingClassifier(other=sklearn.ensemble.forest.RandomForestClassifier,lr=sklearn.linear_model.logistic.LogisticRegression) (1)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.voting_classifier.VotingClassifier(knn=sklearn.neighbors.classification.KNeighborsClassifier,svc=sklearn.pipeline.Pipeline(preprocessing=sklearn.preprocessing.data.RobustScaler,dimension_reduction=sklearn.decomposition.pca.PCA,classifier=sklearn.svm.classes.SVC)) (1)
Automatically created scikit-learn flow.
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