OpenML
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21333 results
weka.Bagging_FilteredClassifier_LMT (1)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
7 runs0 likes0 downloads0 reach6 impact
weka.FilteredClassifier_SMO_PolyKernel (1)
Weka implementation of FilteredClassifier
277 runs0 likes0 downloads0 reach267 impact
weka.CostSensitiveClassifier_AttributeSelectedClassifier_Logistic (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach1 impact
weka.AttributeSelectedClassifier_Logistic (2)
Weka implementation of AttributeSelectedClassifier
3 runs0 likes0 downloads0 reach3 impact
weka.CostSensitiveClassifier_AttributeSelectedClassifier_AdaBoostM1_Logistic (1)
Weka implementation of CostSensitiveClassifier
0 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_AdaBoostM1_Logistic (1)
Weka implementation of AttributeSelectedClassifier
0 runs0 likes0 downloads0 reach0 impact
weka.AdaBoostM1_Logistic (1)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
1 runs0 likes0 downloads0 reach1 impact
weka.RandomizableFilteredClassifier_RandomForest (1)
Weka implementation of RandomizableFilteredClassifier
63 runs0 likes0 downloads0 reach61 impact
weka.RandomizableFilteredClassifier_MultilayerPerceptron (1)
Weka implementation of RandomizableFilteredClassifier
11 runs0 likes0 downloads0 reach7 impact
weka.FilteredClassifier_FilteredClassifier_FilteredClassifier_Logistic (1)
Weka implementation of FilteredClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.Stacking_RandomizableFilteredClassifier (1)
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
1 runs0 likes0 downloads0 reach0 impact
weka.RandomizableFilteredClassifier (1)
Weka implementation of RandomizableFilteredClassifier
0 runs0 likes0 downloads0 reach0 impact
weka.Stacking_IBk (2)
David H. Wolpert (1992). Stacked generalization. Neural Networks. 5:241-259.
1 runs0 likes0 downloads0 reach0 impact
weka.MultiClassClassifier_SMO_RBFKernel (1)
Weka implementation of MultiClassClassifier
1 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_AdaBoostM1_SMO_PolyKernel (1)
Weka implementation of CostSensitiveClassifier
0 runs0 likes0 downloads0 reach0 impact
weka.AdaBoostM1_SMO_PolyKernel (3)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
0 runs0 likes0 downloads0 reach0 impact
weka.SMO_PolyKernel (16)
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,…
0 runs0 likes0 downloads0 reach0 impact
weka.PolyKernel (12)
Weka implementation of PolyKernel
0 runs0 likes0 downloads0 reach0 impact
weka.DecisionTable (4)
Ron Kohavi: The Power of Decision Tables. In: 8th European Conference on Machine Learning, 174-189, 1995.
3 runs0 likes0 downloads0 reach1 impact
weka.AdaBoostM1_CostSensitiveClassifier_Logistic (2)
Yoav Freund, Robert E. Schapire: Experiments with a new boosting algorithm. In: Thirteenth International Conference on Machine Learning, San Francisco, 148-156, 1996.
1 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_Logistic (4)
Weka implementation of CostSensitiveClassifier
1 runs0 likes0 downloads0 reach1 impact
weka.Logistic (9)
le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
0 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_MultiBoostAB_RandomForest (1)
Weka implementation of CostSensitiveClassifier
1 runs0 likes0 downloads0 reach0 impact
weka.MultiBoostAB_RandomForest (3)
Geoffrey I. Webb (2000). MultiBoosting: A Technique for Combining Boosting and Wagging. Machine Learning. Vol.40(No.2).
1 runs0 likes0 downloads0 reach1 impact
weka.CostSensitiveClassifier_FilteredClassifier_Bagging_Logistic (1)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach0 impact
weka.FilteredClassifier_Bagging_Logistic (1)
Weka implementation of FilteredClassifier
0 runs0 likes0 downloads0 reach0 impact
weka.Bagging_Logistic (2)
Leo Breiman (1996). Bagging predictors. Machine Learning. 24(2):123-140.
0 runs0 likes0 downloads0 reach0 impact
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.FilteredClassifier_FilteredClassifier_SMO_PolyKernel (1)
Weka implementation of FilteredClassifier
4 runs0 likes0 downloads0 reach0 impact
weka.FilteredClassifier_SMO_RBFKernel (1)
Weka implementation of FilteredClassifier
159 runs0 likes0 downloads0 reach142 impact
weka.RandomizableFilteredClassifier_SMO_PolyKernel (1)
Weka implementation of RandomizableFilteredClassifier
21 runs0 likes0 downloads0 reach5 impact
weka.RandomizableFilteredClassifier_Bagging_RandomForest (1)
Weka implementation of RandomizableFilteredClassifier
9 runs0 likes0 downloads0 reach4 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.RandomizableFilteredClassifier_J48 (1)
Weka implementation of RandomizableFilteredClassifier
13 runs0 likes0 downloads0 reach4 impact
weka.RandomizableFilteredClassifier_LMT (1)
Weka implementation of RandomizableFilteredClassifier
8 runs0 likes0 downloads0 reach3 impact
weka.AdaBoostM1_AttributeSelectedClassifier_CostSensitiveClassifier_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.
0 runs0 likes0 downloads0 reach0 impact
weka.AttributeSelectedClassifier_CostSensitiveClassifier_RandomForest (1)
Weka implementation of AttributeSelectedClassifier
0 runs0 likes0 downloads0 reach0 impact
weka.CostSensitiveClassifier_RandomForest (6)
Weka implementation of CostSensitiveClassifier
2 runs0 likes0 downloads0 reach2 impact
weka.CostSensitiveClassifier_FilteredClassifier_IBk (1)
Weka implementation of CostSensitiveClassifier
1 runs0 likes0 downloads0 reach0 impact
keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,MaxPooling2D,Conv2D,MaxPooling2D,Flatten,Dense,Activation,Dense,Activation) (3)
Automatically created scikit-learn flow.
6 runs0 likes0 downloads0 reach0 impact
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Dense,Dense) (1)
Automatically created scikit-learn flow.
6 runs0 likes0 downloads0 reach0 impact
mlr.classif.rpart (52)
Learner mlr.classif.rpart from package(s) rpart.
1 runs0 likes0 downloads0 reach0 impact
sklearn.neural_network.multilayer_perceptron.MLPClassifier (14)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,Conv2D,MaxPooling2D,Activation,Flatten,Dense,Dense,Dense) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,kerasclassifier=keras.wrappers.scikit_learn.KerasClassifier) (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
keras.wrappers.scikit_learn.KerasClassifier (8)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
mlr.classif.randomForest (42)
Learner mlr.classif.randomForest from package(s) randomForest.
0 runs0 likes0 downloads0 reach0 impact
sklearn.tree.tree.ExtraTreeClassifier (17)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach1 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (18)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach1 impact
sklearn.preprocessing.imputation.Imputer (25)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing.data.OneHotEncoder (25)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.forest.RandomForestClassifier (39)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (2)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
sklearn.neighbors.classification.KNeighborsClassifier (26)
Automatically created scikit-learn flow.
3 runs0 likes0 downloads0 reach0 impact
sklearn.dummy.DummyClassifier (8)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
keras.wrappers.scikit_learn.KerasClassifier(InputLayer,Reshape,ZeroPadding2D,Conv2D,Conv2D,BatchNormalization,Activation,Conv2D,BatchNormalization,Add,Activation,Conv2D,BatchNormalization,Activation,Conv2D,BatchNormalization,Add,Activation,Conv2D,BatchNormalization,Activation,Conv2D,Conv2D,BatchNormalization,Add,Activation,Conv2D,BatchNormalization,Activation,Conv2D,BatchNormalization,Add,Activation,Conv2D,BatchNormalization,Activation,Conv2D,Conv2D,BatchNormalization,Add,Activation,Conv2D,BatchNormalization,Activation,Conv2D,BatchNormalization,Add,Activation,AveragePooling2D,Flatten,Dense) (3)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(standardscaler=sklearn.preprocessing.data.StandardScaler,kerasclassifier=keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,MaxPooling2D,Conv2D,MaxPooling2D,Flatten,Dense,Activation,Dense,Activation)) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
keras.wrappers.scikit_learn.KerasClassifier(Reshape,Conv2D,MaxPooling2D,Conv2D,MaxPooling2D,Flatten,Dense,Activation,Dense,Activation) (4)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
__main__.GradientBoostingClassifierBOHB (1)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
__main__.RandomForestWithPCA (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
__main__.GradientBoostingWithPCA (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier)) (3)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
openmlstudy14.preprocessing.ConditionalImputer (8)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier) (5)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.tree.tree.DecisionTreeClassifier (24)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier))) (3)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.ensemble.forest.RandomForestClassifier (40)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier)) (4)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
xgboost.sklearn.XGBClassifier (7)
Automatically created scikit-learn flow.
5 runs0 likes0 downloads0 reach3 impact
keras.wrappers.scikit_learn.KerasClassifier(Reshape,Lambda,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Flatten,Dense,Dropout,Dense,Dropout,Dense) (1)
Automatically created scikit-learn flow.
7 runs0 likes0 downloads0 reach0 impact
keras.wrappers.scikit_learn.KerasClassifier(Reshape,Lambda,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Conv2D,Conv2D,Conv2D,MaxPooling2D,BatchNormalization,Flatten,Dense,Dropout,Dense,Dropout,Dense) (2)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach0 impact
__main__.NNAugmentedInput (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.tree.tree.ExtraTreeClassifier (18)
Automatically created scikit-learn flow.
10 runs0 likes0 downloads0 reach10 impact
sklearn.svm.classes.LinearSVC (8)
Automatically created scikit-learn flow.
1 runs0 likes0 downloads0 reach0 impact
openmlstudy99.preprocessing.ConditionalImputer (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
openmldefaults.search.default_search.DefaultSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.weight_boosting.AdaBoostClassifier(base_estimator=sklearn.tree.tree.DecisionTreeClassifier))) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.neighbors.classification.KNeighborsClassifier (27)
Automatically created scikit-learn flow.
4 runs0 likes0 downloads0 reach3 impact
sklearn.ensemble.forest.RandomForestClassifier (41)
Automatically created scikit-learn flow.
12 runs0 likes0 downloads0 reach12 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (19)
Automatically created scikit-learn flow.
7 runs0 likes0 downloads0 reach6 impact
sklearn.preprocessing.imputation.Imputer (26)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing.data.OneHotEncoder (26)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
openmldefaults.search.default_search.DefaultSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.ensemble.forest.RandomForestClassifier)) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(Imputer=sklearn.preprocessing.imputation.Imputer,OneHotEncoder=sklearn.preprocessing.data.OneHotEncoder,Classifier=sklearn.ensemble.forest.RandomForestClassifier) (20)
Automatically created scikit-learn flow.
2 runs0 likes0 downloads0 reach1 impact
openmldefaults.search.default_search.DefaultSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)) (1)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC) (3)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.preprocessing.data.StandardScaler (10)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,classifier=sklearn.svm.classes.SVC)) (2)
Automatically created scikit-learn flow.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.RBFKernel,weka.classifiers.functions.Logistic))) (1)
Weka implementation.
63 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.multisearch.RandomSearch (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize),weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.RBFKernel,weka.classifiers.functions.Logistic)) (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingValues,weka.filters.unsupervised.attribute.RemoveUseless,weka.filters.unsupervised.attribute.Normalize) (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.filters.unsupervised.attribute.ReplaceMissingValues (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.filters.unsupervised.attribute.RemoveUseless (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.filters.unsupervised.attribute.Normalize (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.functions.SMO(weka.classifiers.functions.supportVector.RBFKernel,weka.classifiers.functions.Logistic) (1)
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,…
67 runs0 likes0 downloads0 reach0 impact
weka.classifiers.functions.supportVector.RBFKernel (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.functions.Logistic (1)
le Cessie, S., van Houwelingen, J.C. (1992). Ridge Estimators in Logistic Regression. Applied Statistics. 41(1):191-201.
0 runs0 likes0 downloads0 reach0 impact
weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,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))) (1)
Weka implementation.
6 runs0 likes0 downloads0 reach0 impact
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)) (1)
Weka implementation.
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weka.classifiers.trees.REPTree (1)
Weka implementation.
0 runs0 likes0 downloads0 reach0 impact