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Classification on OT 50% corrupted features (50% noise)

81.7AccuracyLassoNet + FT
77.64478.69779.7580.803Mar 21, 2026

Evaluation results

MethodLinks
LassoNet + FTFeature Selection=LassoNet, Downstream Model=FT-Transformer2026.0381.7
Lasso + FTFeature Selection=Lasso, Downstream Model=FT-Transformer2026.0381.6
1L Lasso + FTFeature Selection=1L Lasso, Downstream Model=FT-Transformer2026.0381.6
RF + FTFeature Selection=RF, Downstream Model=FT-Transformer2026.0381.6
AGL + FTFeature Selection=AGL, Downstream Model=FT-Transformer2026.0381.3
Univariate + FTFeature Selection=Univariate, Downstream Model=FT-Transformer2026.0381.2
No FS + FTFeature Selection=None, Downstream Model=FT-Transformer2026.0380.9
XGBoost + FTFeature Selection=XGBoost, Downstream Model=FT-Transformer2026.0380.9
LassoFlexNetFeature Selection=End-to-end2026.0380.9
AM + FTFeature Selection=AM, Downstream Model=FT-Transformer2026.0380.6
XGBoost + MLPFeature Selection=XGBoost, Downstream Model=MLP2026.0380.3
Deep Lasso + MLPFeature Selection=Deep Lasso, Downstream Model=MLP2026.0380.1
Deep Lasso + FTFeature Selection=Deep Lasso, Downstream Model=FT-Transformer2026.0380.1
AM + MLPFeature Selection=AM, Downstream Model=MLP2026.0379.7
Lasso + MLPFeature Selection=Lasso, Downstream Model=MLP2026.0379.6
AGL + MLPFeature Selection=AGL, Downstream Model=MLP2026.0379.6
Univariate + MLPFeature Selection=Univariate, Downstream Model=MLP2026.0379.5
1L Lasso + MLPFeature Selection=1L Lasso, Downstream Model=MLP2026.0379.5
LassoNet + MLPFeature Selection=LassoNet, Downstream Model=MLP2026.0379.5
RF + MLPFeature Selection=RF, Downstream Model=MLP2026.0378.8
No FS + MLPFeature Selection=None, Downstream Model=MLP2026.0377.8