OpenML-CC18: mfeat-fourier
Best predictive accuracy per machine-learning flow on the mfeat-fourier classification task from the OpenML-CC18 suite.
Community results for the mfeat-fourier classification task from OpenML-CC18, OpenML's curated suite of 72 classification tasks (www.openml.org/t/14). 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 41 measurements, ranked by average.
| Subject | Avg | Median | Min | Max | P95 | P99 | Count |
|---|---|---|---|---|---|---|---|
| sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold… | 0.8805 | 0.8805 | 0.8805 | 0.8805 | 0.8805 | 0.8805 | 1 |
| sklearn.svm.classes.SVC(5) | 0.8765 | 0.8765 | 0.8765 | 0.8765 | 0.8765 | 0.8765 | 1 |
| sklearn.svm.classes.SVC(32) | 0.876 | 0.876 | 0.876 | 0.876 | 0.876 | 0.876 | 1 |
| weka.AttributeSelectedClassifier_SMO_PolyKernel(2) | 0.866 | 0.866 | 0.866 | 0.866 | 0.866 | 0.866 | 1 |
| weka.FilteredClassifier_AttributeSelectedClassifier_SMO_PolyKernel(1) | 0.862 | 0.862 | 0.862 | 0.862 | 0.862 | 0.862 | 1 |
| sklearn.svm.classes.SVC(31) | 0.858 | 0.858 | 0.858 | 0.858 | 0.858 | 0.858 | 1 |
| sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1) | 0.857 | 0.857 | 0.857 | 0.857 | 0.857 | 0.857 | 1 |
| weka.FilteredClassifier_AttributeSelectedClassifier_RandomForest(1) | 0.854 | 0.854 | 0.854 | 0.854 | 0.854 | 0.854 | 1 |
| sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifi… | 0.8535 | 0.8535 | 0.8535 | 0.8535 | 0.8535 | 0.8535 | 1 |
| sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold… | 0.853 | 0.853 | 0.853 | 0.853 | 0.853 | 0.853 | 1 |
| sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(4) | 0.8525 | 0.8525 | 0.8525 | 0.8525 | 0.8525 | 0.8525 | 1 |
| sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2) | 0.8525 | 0.8525 | 0.8525 | 0.8525 | 0.8525 | 0.8525 | 1 |
| sklearn.pipeline.Pipeline(imputation=openmlstudy14.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshold… | 0.8525 | 0.8525 | 0.8525 | 0.8525 | 0.8525 | 0.8525 | 1 |
| sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3) | 0.852 | 0.852 | 0.852 | 0.852 | 0.852 | 0.852 | 1 |
| sklearn.model_selection._search.RandomizedSearchCV(estimator=sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,… | 0.852 | 0.852 | 0.852 | 0.852 | 0.852 | 0.852 | 1 |
| sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_thresho… | 0.852 | 0.852 | 0.852 | 0.852 | 0.852 | 0.852 | 1 |
| sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,variencethreshold=sklearn.feature_selection.variance_threshol… | 0.852 | 0.852 | 0.852 | 0.852 | 0.852 | 0.852 | 1 |
| weka.SMO_RBFKernel(1) | 0.852 | 0.852 | 0.852 | 0.852 | 0.852 | 0.852 | 1 |
| weka.SMO_PolyKernel(1) | 0.8515 | 0.8515 | 0.8515 | 0.8515 | 0.8515 | 0.8515 | 1 |
| weka.AttributeSelectedClassifier_Bagging_LMT(1) | 0.85 | 0.85 | 0.85 | 0.85 | 0.85 | 0.85 | 1 |
| sklearn.model_selection._search_successive_halving.HalvingRandomSearchCV(estimator=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(3) | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 1 |
| weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingVa… | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 1 |
| sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1) | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 1 |
| sklearn.pipeline.Pipeline(columntransformer=sklearn.compose._column_transformer.ColumnTransformer(numeric=sklearn.pipeline.Pipeline(imputer=sklearn.preprocessing.imputation.Imputer,standardscaler=skl… | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 1 |
| sklearn.pipeline.Pipeline(imputation=preprocessing.ConditionalImputer2,catencoding=preprocessing.MultiLabelEncoder,variencethreshold=sklearn.feature_selection.variance_threshold.VarianceThreshold,clf… | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 0.8495 | 1 |
…and 16 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 (41)
- sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier(2)
- 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=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(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(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=hyperimp.utils.preprocessing.ConditionalImputer2,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,varienceth…
- sklearn.pipeline.Pipeline(imputation=hyperimp.utils.preprocessing.ConditionalImputer,hotencoding=sklearn.preprocessing.data.OneHotEncoder,scaling=sklearn.preprocessing.data.StandardScaler,variencethr…
- 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,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=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,histgradientboostingclassifier=sklearn.ensemble._hist_gradient_boosting.gradient_boosting.HistGradientBoostingClassifier)(1)
- sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,randomforestclassifier=sklearn.ensemble.forest.RandomForestClassifi…
- sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(4)
- sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(1)
- sklearn.pipeline.Pipeline(simpleimputer=sklearn.impute._base.SimpleImputer,standardscaler=sklearn.preprocessing.data.StandardScaler,svc=sklearn.svm.classes.SVC)(2)
- sklearn.svm.classes.SVC(31)
- sklearn.svm.classes.SVC(32)
- sklearn.svm.classes.SVC(35)
- sklearn.svm.classes.SVC(5)
- weka.AttributeSelectedClassifier_Bagging_LMT(1)
- weka.AttributeSelectedClassifier_RandomForest(1)
- weka.AttributeSelectedClassifier_RandomForest(2)
- weka.AttributeSelectedClassifier_SMO_PolyKernel(2)
- weka.Bagging_LMT(2)
- weka.classifiers.meta.MultiSearch(weka.classifiers.meta.multisearch.RandomSearch,weka.classifiers.meta.FilteredClassifier(weka.filters.MultiFilter(weka.filters.unsupervised.attribute.ReplaceMissingVa…
- weka.FilteredClassifier_AttributeSelectedClassifier_Bagging_LMT(1)
- weka.FilteredClassifier_AttributeSelectedClassifier_RandomForest(1)
- weka.FilteredClassifier_AttributeSelectedClassifier_SMO_PolyKernel(1)
- weka.FilteredClassifier_SMO_PolyKernel(1)
- weka.kf.AttributeSelection-Ranker-InfoGain-SMO(1)
- weka.SMO_PolyKernel(1)
- weka.SMO_PolyKernel(15)
- weka.SMO_RBFKernel(1)
Published by OpenML.
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