Regression on YE 50% corrupted features noise
-0.776Negative RMSEDeep Lasso + MLP
Evaluation results
| Method | Links | |
|---|---|---|
| Deep Lasso + MLPFeature Selection=Deep Lasso, Downstream Model=MLP2026.03 | -0.776 | |
| Deep Lasso + FTFeature Selection=Deep Lasso, Downstream Model=FT-Transformer2026.03 | -0.776 | |
| LassoNet + MLPFeature Selection=LassoNet, Downstream Model=MLP2026.03 | -0.777 | |
| XGBoost + MLPFeature Selection=XGBoost, Downstream Model=MLP2026.03 | -0.779 | |
| 1L Lasso + MLPFeature Selection=1L Lasso, Downstream Model=MLP2026.03 | -0.78 | |
| AGL + MLPFeature Selection=AGL, Downstream Model=MLP2026.03 | -0.78 | |
| AM + MLPFeature Selection=AM, Downstream Model=MLP2026.03 | -0.78 | |
| LassoFlexNetFeature Selection=End-to-end2026.03 | -0.78 | |
| RF + MLPFeature Selection=RF, Downstream Model=MLP2026.03 | -0.786 | |
| XGBoost + FTFeature Selection=XGBoost, Downstream Model=FT-Transformer2026.03 | -0.788 | |
| AGL + FTFeature Selection=AGL, Downstream Model=FT-Transformer2026.03 | -0.79 | |
| LassoNet + FTFeature Selection=LassoNet, Downstream Model=FT-Transformer2026.03 | -0.79 | |
| RF + FTFeature Selection=RF, Downstream Model=FT-Transformer2026.03 | -0.79 | |
| AM + FTFeature Selection=AM, Downstream Model=FT-Transformer2026.03 | -0.793 | |
| Lasso + MLPFeature Selection=Lasso, Downstream Model=MLP2026.03 | -0.795 | |
| Lasso + FTFeature Selection=Lasso, Downstream Model=FT-Transformer2026.03 | -0.795 | |
| No FS + MLPFeature Selection=None, Downstream Model=MLP2026.03 | -0.797 | |
| No FS + FTFeature Selection=None, Downstream Model=FT-Transformer2026.03 | -0.826 | |
| Univariate + MLPFeature Selection=Univariate, Downstream Model=MLP2026.03 | -0.828 | |
| 1L Lasso + FTFeature Selection=1L Lasso, Downstream Model=FT-Transformer2026.03 | -0.83 | |
| Univariate + FTFeature Selection=Univariate, Downstream Model=FT-Transformer2026.03 | -0.915 |