Refractive Index (n2) Regression on EllipBench
0.237MAEDCFM
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| DCFMMethodological Paradigm=Physics Informed Method2024.07 | 0.237 | 0.428 | 0.9 | |
| Random ForestMethodological Paradigm=Ensemble Learning Method2024.07 | 0.246 | 0.441 | 0.894 | |
| MLPMethodological Paradigm=Deep Learning Method2024.07 | 0.278 | 0.437 | 0.896 | |
| TransformerMethodological Paradigm=Deep Learning Method2024.07 | 0.279 | 0.441 | 0.894 | |
| LightGBMMethodological Paradigm=Ensemble Learning Method2024.07 | 0.313 | 0.489 | 0.87 | |
| XGBoostMethodological Paradigm=Ensemble Learning Method2024.07 | 0.319 | 0.495 | 0.867 | |
| Support Vector RegressorMethodological Paradigm=Conventional Regression Method2024.07 | 0.41 | 0.663 | 0.761 | |
| PINNMethodological Paradigm=Physics Informed Method2024.07 | 0.622 | 0.882 | 0.577 | |
| Ridge RegressionMethodological Paradigm=Conventional Regression Method2024.07 | 0.927 | 1.26 | 0.137 | |
| ElasticNet RegressionMethodological Paradigm=Conventional Regression Method2024.07 | 0.927 | 1.26 | 0.137 |