OpenML-CC18: cmc
Best predictive accuracy per machine-learning flow on the cmc classification task from the OpenML-CC18 suite.
Community results for the cmc classification task from OpenML-CC18, OpenML's curated suite of 72 classification tasks (www.openml.org/t/23). Each subject 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.
Results
predictive_accuracy per subject over 61 measurements, ranked by average.
| Subject | Avg | Median | Min | Max | P95 | P99 | Count |
|---|---|---|---|---|---|---|---|
| weka.AttributeSelectedClassifier_LWL_MultilayerPerceptron(1) | 0.5764 | 0.5764 | 0.5764 | 0.5764 | 0.5764 | 0.5764 | 1 |
| sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(simpleimputer=sklearn.impute._base.SimpleImputer,onehotencoder=sklearn.preprocessing._encoders.OneHot… | 0.5743 | 0.5743 | 0.5743 | 0.5743 | 0.5743 | 0.5743 | 1 |
| sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_thresho… | 0.5737 | 0.5737 | 0.5737 | 0.5737 | 0.5737 | 0.5737 | 1 |
| sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshol… | 0.573 | 0.573 | 0.573 | 0.573 | 0.573 | 0.573 | 1 |
| sklearn.pipeline.Pipeline(pca=sklearn.decomposition.pca.PCA,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1) | 0.5709 | 0.5709 | 0.5709 | 0.5709 | 0.5709 | 0.5709 | 1 |
| sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=skl… | 0.5709 | 0.5709 | 0.5709 | 0.5709 | 0.5709 | 0.5709 | 1 |
| sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3) | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 1 |
| sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.neural_network._multilayer_perceptron.MLPClassifier)(2) | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 1 |
| sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1) | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 1 |
| sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold… | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 0.5703 | 1 |
| sklearn.pipeline.Pipeline(dualimputer=extra.dual_imputer.DualImputer,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1) | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 1 |
| sklearn.pipeline.Pipeline(DualImputer=helper.dual_imputer.DualImputer,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1) | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 1 |
| sklearn.pipeline.Pipeline(gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1) | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 1 |
| sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=xgboost.sklearn.XGBClassifier)(1) | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 0.5689 | 1 |
| sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,v… | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 1 |
| sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,v… | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 1 |
| sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold… | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 1 |
| weka-filteredclassifier-ladtree-1 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 1 |
| sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing.data.OneHotEncoder,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1) | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 1 |
| weka-ladtree-7 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 1 |
| weka-ladtree-4 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 1 |
| weka-ladtree-1 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 0.5682 | 1 |
| sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,columntransformer=sklearn.compose._column_transformer.ColumnTransformer(num=sklearn.pipeline.Pipeline(standardscaler=sklearn… | 0.5675 | 0.5675 | 0.5675 | 0.5675 | 0.5675 | 0.5675 | 1 |
| sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=skl… | 0.5669 | 0.5669 | 0.5669 | 0.5669 | 0.5669 | 0.5669 | 1 |
| sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=skl… | 0.5669 | 0.5669 | 0.5669 | 0.5669 | 0.5669 | 0.5669 | 1 |
…and 36 more subjects.
Metrics
- predictive_accuracy — recorded on each measurement. Best predictive accuracy this flow achieved on the task: the fraction of test instances classified correctly, from 0 to 1. Higher is better
Subjects (61)
- classif.boosting(4)
- classif.cforest(4)
- mlr.classif.earth.preproc(1)
- mlr.classif.rpart.preproc(16)
- openmlpimp.sklearn.beam_search.BeamSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,varience…
- sklearn.ensemble.gradient_boosting.GradientBoostingClassifier(3)
- 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=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.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,onehotencoder=sklearn.preprocessing.data.OneHotEncoder,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)
- sklearn.pipeline.Pipeline(DualImputer=helper.dual_imputer.DualImputer,gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)
- sklearn.pipeline.Pipeline(gradientboostingclassifier=sklearn.ensemble.gradient_boosting.GradientBoostingClassifier)(1)
- 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.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshol…
- 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(imputer=sklearn.impute._base.SimpleImputer,estimator=sklearn.neural_network._multilayer_perceptron.MLPClassifier)(2)
- sklearn.pipeline.Pipeline(imputer=sklearn.impute._base.SimpleImputer,estimator=xgboost.sklearn.XGBClassifier)(1)
- sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing.data.OneHotEncoder,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)
- sklearn.pipeline.Pipeline(pca=sklearn.decomposition.pca.PCA,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifier)(1)
- sklearn.pipeline.Pipeline(Preprocessing=sklearn.compose._column_transformer.ColumnTransformer(categorical=sklearn.pipeline.Pipeline(onehotencoder=sklearn.preprocessing._encoders.OneHotEncoder,simplei…
- 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)
- sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkceigenpro=sklearn_extra.fast_kernel.FKCEigenPro)(1)
- sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,fkc_eigenpro=sklearn_extra.fast_kernel.FKC_EigenPro)(1)
- sklearn.svm.classes.SVC(45)
- weka.AdaBoostM1_LADTree(1)
- weka.AdaBoostM1_LADTree(2)
- weka.AttributeSelectedClassifier_Bagging_MultilayerPerceptron(1)
- weka.AttributeSelectedClassifier_ClassificationViaRegression_M5P(1)
- weka.AttributeSelectedClassifier_IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)
- weka.AttributeSelectedClassifier_LADTree(1)
- weka.AttributeSelectedClassifier_LMT(2)
- weka.AttributeSelectedClassifier_LogitBoost_DecisionStump(1)
- weka.AttributeSelectedClassifier_LWL_MultilayerPerceptron(1)
- weka.AttributeSelectedClassifier_MultilayerPerceptron(2)
- weka.AttributeSelectedClassifier_SMO_PolyKernel(2)
- weka.Bagging_LADTree(1)
- weka.FilteredClassifier_AttributeSelectedClassifier_ClassificationViaRegression_M5P(1)
- weka.FilteredClassifier_AttributeSelectedClassifier_IterativeClassifierOptimizer_LogitBoost_DecisionStump(1)
- weka.FilteredClassifier_AttributeSelectedClassifier_LADTree(1)
- weka.FilteredClassifier_AttributeSelectedClassifier_LogitBoost_DecisionStump(1)
…and 11 more.
Published by OpenML.
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