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

0.801Downstream Performance

Deep Lasso + MLP

Updated 4d ago

Evaluation Results

Method	Links
Deep Lasso + MLP 2023.11		0.801	1.91
AGL + MLP 2023.11		0.8	3.36
XGBoost + MLP 2023.11		0.8	2.64
1L Lasso + MLP 2023.11		0.798	3.09
Deep Lasso + MLP 2023.11		0.798	2
Lasso + MLP 2023.11		0.797	6.55
LassoNet + MLP 2023.11		0.797	4.45
XGBoost + MLP 2023.11		0.797	2
Lasso + MLP 2023.11		0.796	4.36
AM + MLP 2023.11		0.795	3.91
AGL + MLP 2023.11		0.792	3.09
Univariate + MLP 2023.11		0.791	7
1L Lasso + MLP 2023.11		0.791	3.73
LassoNet + MLP 2023.11		0.791	5.09
RF + MLP 2023.11		0.789	5
No FS + MLP 2023.11		0.781	8.27
Univariate + MLP 2023.11		0.779	7.64
RF + MLP 2023.11		0.77	4.45
No FS + MLP 2023.11		0.765	7.73