Regression on HO 75% corrupted features
-0.563Negative RMSEDeep Lasso + MLP
Evaluation Results
| Method | Links | |
|---|---|---|
| Deep Lasso + MLPFeature Selection=Deep Lasso, Downstream Model=MLP2026.03 | -0.563 | |
| XGBoost + MLPFeature Selection=XGBoost, Downstream Model=MLP2026.03 | -0.571 | |
| LassoNet + MLPFeature Selection=LassoNet, Downstream Model=MLP2026.03 | -0.572 | |
| RF + MLPFeature Selection=RF, Downstream Model=MLP2026.03 | -0.573 | |
| AGL + MLPFeature Selection=AGL, Downstream Model=MLP2026.03 | -0.574 | |
| 1L Lasso + MLPFeature Selection=1L Lasso, Downstream Model=MLP2026.03 | -0.576 | |
| LassoFlexNetFeature Selection=End-to-end2026.03 | -0.588 | |
| Lasso + MLPFeature Selection=Lasso, Downstream Model=MLP2026.03 | -0.593 | |
| Univariate + MLPFeature Selection=Univariate, Downstream Model=MLP2026.03 | -0.62 | |
| No FS + MLPFeature Selection=None, Downstream Model=MLP2026.03 | -0.632 |