smplmark

OpenML-CC18: credit-approval

Best predictive accuracy per machine-learning flow on the credit-approval classification task from the OpenML-CC18 suite.

Community results for the credit-approval classification task from OpenML-CC18, OpenML's curated suite of 72 classification tasks (www.openml.org/t/29). Each target is a flow — a specific algorithm or pipeline — shown with the best predictive accuracy recorded for it on this task in OpenML's public evaluation listing, under the task's fixed estimation procedure.

Metrics

  • predictive_accuracy

Targets (50)

  • classif.ada(9)
  • classif.randomForest(57)
  • classif.ranger(8)
  • mlr.classif.ranger.imputed.dummied.preproc(1)
  • mlr.classif.RRF.imputed.dummied.preproc(1)
  • sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)
  • sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)
  • sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,v…
  • sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,…
  • sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4)
  • sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3)
  • sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHot…
  • sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=skl…
  • sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=skl…
  • sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=skl…
  • sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=skl…
  • sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=skl…
  • sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=skl…
  • sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)
  • sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(2)
  • sklearn.pipeline.Pipeline(DualImputer=helper.dual_imputer.DualImputer,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)
  • sklearn.pipeline.Pipeline(dualimputer=helper.dual_imputer.DualImputer,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)
  • sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshol…
  • sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_thresho…
  • sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,varienceth…
  • sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold…
  • sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold…
  • sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethre…
  • sklearn.pipeline.Pipeline(imputation=preprocessing.ConditionalImputer2,catencoding=preprocessing.MultiLabelEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf…
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn…
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn…
  • sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)
  • weka.AdaBoostM1_BFTree(1)
  • weka.AdaBoostM1_BFTree(2)
  • weka.Bagging_JRip(1)
  • weka.Bagging_JRip(2)
  • weka.Bagging_RandomForest(2)
  • weka.FilteredClassifier_AttributeSelectedClassifier_MultiBoostAB_JRip(1)
  • weka.FilteredClassifier_Bagging_JRip(1)
  • weka.FilteredClassifier_MultiSearch_RandomForest(1)
  • weka.FilteredClassifier_RandomForest(4)
  • weka.MultiBoostAB_BFTree(1)
  • weka.MultiBoostAB_DecisionStump(2)
  • weka.MultiBoostAB_DecisionStump(3)
  • weka.MultiBoostAB_LWL_DecisionStump(1)
  • weka.RandomForest(12)
  • weka.RandomForest(9)
  • weka.RandomSubSpace_REPTree(4)
  • weka.RotationForest_PrincipalComponents_J48(14)
  • weka.RotationForest_PrincipalComponents_J48(3)

Published by OpenML.