Classification on australian (accuracy)
91.4AccuracyBAEN-SVM
Evaluation Results
| Method | Links | |
|---|---|---|
| BAEN-SVMKernel=RBF, Noise level=25%, Noise type=label noise2026.04 | 91.4 | |
| ε-BAEN SVMKernel=RBF, Noise level=25%, Noise type=label noise2026.04 | 91.4 | |
| BQ-SVMKernel=RBF, Noise level=25%, Noise type=label noise2026.04 | 90.5 | |
| BALS-SVMKernel=RBF, Noise level=25%, Noise type=label noise2026.04 | 90.5 | |
| Pin-SVMKernel=RBF, Noise level=25%, Noise type=label noise2026.04 | 89.5 | |
| ALS-SVMKernel=RBF, Noise level=25%, Noise type=label noise2026.04 | 89.5 | |
| EN-SVMKernel=RBF, Noise level=25%, Noise type=label noise2026.04 | 89.5 | |
| BALS-SVMKernel=linear, Noise Level=0%2026.04 | 88.1 | |
| BAEN-SVMKernel=linear, Noise Level=0%2026.04 | 88.1 | |
| BALS-SVMKernel=linear, Noise Level=25% feature noise2026.04 | 88 | |
| ALS-SVMKernel=linear, Noise Level=0%2026.04 | 87.8 | |
| ALS-SVMKernel=linear, Noise Level=25% feature noise2026.04 | 87.8 | |
| EN-SVMKernel=linear, Noise Level=25% feature noise2026.04 | 87.8 | |
| ε-BAEN-SVMKernel=linear, Noise Level=25% feature noise2026.04 | 87.7 | |
| BQ-SVMKernel=linear, Noise Level=0%2026.04 | 87.5 | |
| BQ-SVMKernel=linear, Noise Level=25% label noise2026.04 | 87.5 | |
| BAEN-SVMKernel=linear, Noise Level=25% feature noise2026.04 | 87.5 | |
| BAEN-SVMKernel=linear, Noise Level=25% label noise2026.04 | 87.4 | |
| BQ-SVMKernel=linear, Noise Level=25% feature noise2026.04 | 87.4 | |
| BALS-SVMKernel=linear, Noise Level=25% label noise2026.04 | 87.1 | |
| EN-SVMKernel=linear, Noise Level=0%2026.04 | 86.8 | |
| ε-BAEN-SVMKernel=linear, Noise Level=0%2026.04 | 86.8 | |
| Pin-SVMKernel=linear, Noise Level=25% feature noise2026.04 | 86.7 | |
| ALS-SVMKernel=linear, Noise Level=25% label noise2026.04 | 86.4 | |
| Pin-SVMKernel=linear, Noise Level=25% label noise2026.04 | 86.2 | |
| ε-BAEN-SVMKernel=linear, Noise Level=25% label noise2026.04 | 86.1 | |
| CfsSubset Eval-F(#)Classification Algorithm=KNN2026.03 | 86.09 | |
| Pin-SVMKernel=linear, Noise Level=0%2026.04 | 85.7 | |
| EN-SVMKernel=linear, Noise Level=25% label noise2026.04 | 85.7 | |
| CfsSubset Eval-F(#)Classification Algorithm=Linear SVM2026.03 | 85.51 | |
| RSFSAID-F(#)Classification Algorithm=Linear SVM2026.03 | 85.51 | |
| OriginalClassification Algorithm=Linear SVM2026.03 | 85.36 | |
| FARNem-F(#)Classification Algorithm=Linear SVM2026.03 | 85.36 | |
| WARA-F(#)Classification Algorithm=Linear SVM2026.03 | 85.22 | |
| FSbuHD-F(#)Classification Algorithm=Linear SVM2026.03 | 85.22 | |
| FSbuHD-F(#)Classification Algorithm=KNN2026.03 | 84.35 | |
| FSbuHD-F(#)Classification Algorithm=Complex Tree2026.03 | 84.35 | |
| WARA-F(#)Classification Algorithm=Complex Tree2026.03 | 83.48 | |
| WARA-F(#)Classification Algorithm=KNN2026.03 | 83.19 | |
| RSFSAID-F(#)Classification Algorithm=Complex Tree2026.03 | 83.19 | |
| RSFSAID-F(#)Classification Algorithm=KNN2026.03 | 83.04 | |
| OriginalClassification Algorithm=Complex Tree2026.03 | 83.04 | |
| FARNem-F(#)Classification Algorithm=Complex Tree2026.03 | 83.04 | |
| OriginalClassification Algorithm=KNN2026.03 | 82.9 | |
| FARNem-F(#)Classification Algorithm=KNN2026.03 | 82.9 | |
| CfsSubset Eval-F(#)Classification Algorithm=Complex Tree2026.03 | 82.75 |