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Regression on CH 50% corrupted features (50% noise)

-0.415Negative RMSELassoFlexNet
-0.4774-0.4612-0.445-0.4288Mar 21, 2026

Evaluation results

MethodLinks
LassoFlexNetFeature Selection=End-to-end2026.03-0.415
1L Lasso + FTFeature Selection=1L Lasso, Downstream Model=FT-Transformer2026.03-0.419
Univariate + FTFeature Selection=Univariate, Downstream Model=FT-Transformer2026.03-0.422
Lasso + FTFeature Selection=Lasso, Downstream Model=FT-Transformer2026.03-0.422
RF + FTFeature Selection=RF, Downstream Model=FT-Transformer2026.03-0.422
XGBoost + FTFeature Selection=XGBoost, Downstream Model=FT-Transformer2026.03-0.422
Deep Lasso + FTFeature Selection=Deep Lasso, Downstream Model=FT-Transformer2026.03-0.422
AM + FTFeature Selection=AM, Downstream Model=FT-Transformer2026.03-0.424
AGL + FTFeature Selection=AGL, Downstream Model=FT-Transformer2026.03-0.426
LassoNet + FTFeature Selection=LassoNet, Downstream Model=FT-Transformer2026.03-0.426
No FS + FTFeature Selection=None, Downstream Model=FT-Transformer2026.03-0.43
1L Lasso + MLPFeature Selection=1L Lasso, Downstream Model=MLP2026.03-0.447
Deep Lasso + MLPFeature Selection=Deep Lasso, Downstream Model=MLP2026.03-0.447
Lasso + MLPFeature Selection=Lasso, Downstream Model=MLP2026.03-0.449
AM + MLPFeature Selection=AM, Downstream Model=MLP2026.03-0.449
AGL + MLPFeature Selection=AGL, Downstream Model=MLP2026.03-0.45
Univariate + MLPFeature Selection=Univariate, Downstream Model=MLP2026.03-0.451
LassoNet + MLPFeature Selection=LassoNet, Downstream Model=MLP2026.03-0.452
RF + MLPFeature Selection=RF, Downstream Model=MLP2026.03-0.453
XGBoost + MLPFeature Selection=XGBoost, Downstream Model=MLP2026.03-0.454
No FS + MLPFeature Selection=None, Downstream Model=MLP2026.03-0.475