Regression on MI 50% corrupted features noise
-0.892Negative RMSEXGBoost + MLP
Evaluation results
| Method | Links | |
|---|---|---|
| XGBoost + MLPFeature Selection=XGBoost, Downstream Model=MLP2026.03 | -0.892 | |
| Deep Lasso + MLPFeature Selection=Deep Lasso, Downstream Model=MLP2026.03 | -0.895 | |
| RF + FTFeature Selection=RF, Downstream Model=FT-Transformer2026.03 | -0.897 | |
| AM + FTFeature Selection=AM, Downstream Model=FT-Transformer2026.03 | -0.898 | |
| XGBoost + FTFeature Selection=XGBoost, Downstream Model=FT-Transformer2026.03 | -0.898 | |
| Deep Lasso + FTFeature Selection=Deep Lasso, Downstream Model=FT-Transformer2026.03 | -0.898 | |
| Lasso + FTFeature Selection=Lasso, Downstream Model=FT-Transformer2026.03 | -0.899 | |
| LassoNet + FTFeature Selection=LassoNet, Downstream Model=FT-Transformer2026.03 | -0.901 | |
| 1L Lasso + MLPFeature Selection=1L Lasso, Downstream Model=MLP2026.03 | -0.902 | |
| AGL + MLPFeature Selection=AGL, Downstream Model=MLP2026.03 | -0.902 | |
| Lasso + MLPFeature Selection=Lasso, Downstream Model=MLP2026.03 | -0.903 | |
| AGL + FTFeature Selection=AGL, Downstream Model=FT-Transformer2026.03 | -0.903 | |
| LassoFlexNetFeature Selection=End-to-end2026.03 | -0.903 | |
| RF + MLPFeature Selection=RF, Downstream Model=MLP2026.03 | -0.904 | |
| LassoNet + MLPFeature Selection=LassoNet, Downstream Model=MLP2026.03 | -0.905 | |
| AM + MLPFeature Selection=AM, Downstream Model=MLP2026.03 | -0.905 | |
| No FS + MLPFeature Selection=None, Downstream Model=MLP2026.03 | -0.909 | |
| 1L Lasso + FTFeature Selection=1L Lasso, Downstream Model=FT-Transformer2026.03 | -0.914 | |
| Univariate + MLPFeature Selection=Univariate, Downstream Model=MLP2026.03 | -0.92 | |
| No FS + FTFeature Selection=None, Downstream Model=FT-Transformer2026.03 | -0.92 | |
| Univariate + FTFeature Selection=Univariate, Downstream Model=FT-Transformer2026.03 | -0.937 |