Surrogate Learning on Synthetic Scenario Case d
0.21MAESurrogate index
Evaluation Results
| Method | Links | ||
|---|---|---|---|
| Surrogate indexvariant=histogram gradient boosting2026.05 | 0.21 | 0.61 | |
| Surrogate samplingvariant=linear2026.05 | 0.4 | 0.66 | |
| Outcome reg.variant=tree2026.05 | 0.66 | 0.4 | |
| Surrogate indexvariant=tree2026.05 | 0.67 | 0.01 | |
| Bound regressionvariant=tree2026.05 | 0.81 | -2.1 | |
| Surrogate indexvariant=linear2026.05 | 1.17 | 0.51 | |
| Outcome reg.variant=linear2026.05 | 1.22 | 0.51 | |
| Bound regressionvariant=linear2026.05 | 1.33 | 0.48 | |
| Reg.-sel.-reg.variant=tree2026.05 | 1.53 | -23.9 | |
| Reg.-sel.-reg.variant=linear2026.05 | 2.35 | -24 |