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ResearchFormerly WizWand

Downstream performance prediction on OT (Otto) corrupted with Laplace noise

0.801Downstream PerformanceDeep Lasso + MLP
0.763560.773280.7830.79272Nov 10, 2023
Updated 8mo ago

Evaluation results

MethodLinks
Deep Lasso + MLPCorruption percentage (%)=502023.110.8011.91
AGL + MLPCorruption percentage (%)=502023.110.83.36
XGBoost + MLPCorruption percentage (%)=502023.110.82.64
1L Lasso + MLPCorruption percentage (%)=502023.110.7983.09
Deep Lasso + MLPCorruption percentage (%)=752023.110.7982
Lasso + MLPCorruption percentage (%)=502023.110.7976.55
LassoNet + MLPCorruption percentage (%)=502023.110.7974.45
XGBoost + MLPCorruption percentage (%)=752023.110.7972
Lasso + MLPCorruption percentage (%)=752023.110.7964.36
AM + MLPCorruption percentage (%)=502023.110.7953.91
AGL + MLPCorruption percentage (%)=752023.110.7923.09
Univariate + MLPCorruption percentage (%)=502023.110.7917
1L Lasso + MLPCorruption percentage (%)=752023.110.7913.73
LassoNet + MLPCorruption percentage (%)=752023.110.7915.09
RF + MLPCorruption percentage (%)=502023.110.7895
No FS + MLPCorruption percentage (%)=502023.110.7818.27
Univariate + MLPCorruption percentage (%)=752023.110.7797.64
RF + MLPCorruption percentage (%)=752023.110.774.45
No FS + MLPCorruption percentage (%)=752023.110.7657.73