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

72.5AccuracyDeep Lasso + FT
54.09258.87163.6568.429Mar 21, 2026

Evaluation results

MethodLinks
Deep Lasso + FTFeature Selection=Deep Lasso, Downstream Model=FT-Transformer2026.0372.5
1L Lasso + FTFeature Selection=1L Lasso, Downstream Model=FT-Transformer2026.0371.8
LassoFlexNetFeature Selection=End-to-end2026.0371.2
RF + FTFeature Selection=RF, Downstream Model=FT-Transformer2026.0371.1
XGBoost + FTFeature Selection=XGBoost, Downstream Model=FT-Transformer2026.0370.6
Lasso + FTFeature Selection=Lasso, Downstream Model=FT-Transformer2026.0369.7
AGL + FTFeature Selection=AGL, Downstream Model=FT-Transformer2026.0369.7
No FS + FTFeature Selection=None, Downstream Model=FT-Transformer2026.0368.6
Univariate + FTFeature Selection=Univariate, Downstream Model=FT-Transformer2026.0368.1
AM + FTFeature Selection=AM, Downstream Model=FT-Transformer2026.0368
LassoNet + FTFeature Selection=LassoNet, Downstream Model=FT-Transformer2026.0367.9
AGL + MLPFeature Selection=AGL, Downstream Model=MLP2026.0358.8
AM + MLPFeature Selection=AM, Downstream Model=MLP2026.0358.3
XGBoost + MLPFeature Selection=XGBoost, Downstream Model=MLP2026.0358.3
Deep Lasso + MLPFeature Selection=Deep Lasso, Downstream Model=MLP2026.0357.7
RF + MLPFeature Selection=RF, Downstream Model=MLP2026.0357.4
LassoNet + MLPFeature Selection=LassoNet, Downstream Model=MLP2026.0357
1L Lasso + MLPFeature Selection=1L Lasso, Downstream Model=MLP2026.0356.6
No FS + MLPFeature Selection=None, Downstream Model=MLP2026.0355.7
Univariate + MLPFeature Selection=Univariate, Downstream Model=MLP2026.0355.6
Lasso + MLPFeature Selection=Lasso, Downstream Model=MLP2026.0354.8