Extinction Coefficient (k2) Regression on EllipBench
0.39MAEDCFM
Evaluation Results
| Method | Links | |||
|---|---|---|---|---|
| DCFMMethodological Paradigm=Physics Informed Method2024.07 | 0.39 | 0.764 | 86.5 | |
| Random ForestMethodological Paradigm=Ensemble Learning Method2024.07 | 0.394 | 0.748 | 87.1 | |
| MLPMethodological Paradigm=Deep Learning Method2024.07 | 0.45 | 0.77 | 86.3 | |
| TransformerMethodological Paradigm=Deep Learning Method2024.07 | 0.464 | 0.776 | 86.1 | |
| LightGBMMethodological Paradigm=Ensemble Learning Method2024.07 | 0.524 | 0.861 | 82.9 | |
| XGBoostMethodological Paradigm=Ensemble Learning Method2024.07 | 0.532 | 0.873 | 82.4 | |
| Support Vector RegressorMethodological Paradigm=Conventional Regression Method2024.07 | 0.681 | 1.225 | 65.3 | |
| PINNMethodological Paradigm=Physics Informed Method2024.07 | 0.788 | 1.133 | 70.3 | |
| Ridge RegressionMethodological Paradigm=Conventional Regression Method2024.07 | 1.288 | 1.661 | 36.2 | |
| ElasticNet RegressionMethodological Paradigm=Conventional Regression Method2024.07 | 1.288 | 1.661 | 36.2 |