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Downstream performance prediction on GE German corrupted with Laplace noise

0.6Downstream Performance

XGBoost + MLP

Updated 4d ago

Evaluation Results

Method	Links
XGBoost + MLP 2023.11		0.6	2.64
RF + MLP 2023.11		0.558	5
XGBoost + MLP 2023.11		0.558	2
LassoNet + MLP 2023.11		0.551	4.45
LassoNet + MLP 2023.11		0.543	5.09
Deep Lasso + MLP 2023.11		0.539	1.91
Univariate + MLP 2023.11		0.531	7
Deep Lasso + MLP 2023.11		0.527	2
AM + MLP 2023.11		0.526	3.91
No FS + MLP 2023.11		0.525	8.27
RF + MLP 2023.11		0.524	4.45
1L Lasso + MLP 2023.11		0.521	3.09
1L Lasso + MLP 2023.11		0.519	3.73
AGL + MLP 2023.11		0.519	3.09
AGL + MLP 2023.11		0.518	3.36
No FS + MLP 2023.11		0.514	7.73
Lasso + MLP 2023.11		0.507	6.55
Univariate + MLP 2023.11		0.493	7.64
Lasso + MLP 2023.11		0.482	4.36