Tabular Regression on Protein UCI 10% outlier contamination
520.6RMSEMacKay
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| MacKayOutlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=10, Model=Heteroscedastic SBL2026.05 | 520.6 | 5.2 | 90.2 | |
| ℓ2-IRLSOutlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=10, Model=Heteroscedastic SBL2026.05 | 524 | 19 | 91.5 | |
| EMOutlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=10, Model=Heteroscedastic SBL2026.05 | 525.8 | 11.7 | 91.7 | |
| Grad. (Primal)Outlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=10, Model=Heteroscedastic SBL2026.05 | 565.1 | 9.8 | 87.1 | |
| Grad. (Dual)Outlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=10, Model=Heteroscedastic SBL2026.05 | 565.5 | 8.2 | 87 | |
| ℓ1-IRLSOutlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=10, Model=Heteroscedastic SBL2026.05 | 601.6 | 7.3 | 92.5 | |
| HuberOutlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=102026.05 | 653.8 | 100 | 88.5 | |
| GPOutlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=102026.05 | 880.5 | 27.7 | 100 | |
| RidgeOutlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=102026.05 | 957.2 | 90.9 | 100 | |
| Student-tOutlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=102026.05 | 1,060.3 | 100 | 89.7 | |
| OLSOutlier Contamination=10%, Feature Mapping=Random Fourier Features (RFF), Dimensions (d)=256, Trials=102026.05 | 2,932.8 | 100 | 100 |