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Downstream performance prediction on JA (Jannis) corrupted with Laplace noise

0.723Downstream Performance

RF + MLP

Updated 4d ago

Evaluation Results

Method	Links
RF + MLP 2023.11		0.723	5
AGL + MLP 2023.11		0.722	3.09
1L Lasso + MLP 2023.11		0.721	3.09
AGL + MLP 2023.11		0.721	3.36
XGBoost + MLP 2023.11		0.721	2
XGBoost + MLP 2023.11		0.72	2.64
Deep Lasso + MLP 2023.11		0.72	1.91
Deep Lasso + MLP 2023.11		0.72	2
AM + MLP 2023.11		0.719	3.91
Lasso + MLP 2023.11		0.718	6.55
Univariate + MLP 2023.11		0.717	7
LassoNet + MLP 2023.11		0.716	4.45
RF + MLP 2023.11		0.716	4.45
Lasso + MLP 2023.11		0.714	4.36
1L Lasso + MLP 2023.11		0.714	3.73
LassoNet + MLP 2023.11		0.712	5.09
No FS + MLP 2023.11		0.704	8.27
Univariate + MLP 2023.11		0.688	7.64
No FS + MLP 2023.11		0.687	7.73