Regression on Wind Power
-8MSE Change (%)CRDA
Evaluation results
| Method | Links | |||
|---|---|---|---|---|
| CRDAModel=MLP2026.06 | -8 | — | — | |
| TabDDPMModel=MLP2026.06 | -7.1 | — | — | |
| CRDAModel=XGB2026.06 | -2.6 | — | — | |
| C-MixupModel=XGB2026.06 | -1.9 | — | — | |
| TabDDPMModel=XGB2026.06 | -0.4 | — | — | |
| ADAModel=XGB2026.06 | -0.2 | — | — | |
| TVAEModel=XGB2026.06 | 4.8 | — | — | |
| C-MixupModel=MLP2026.06 | 4.9 | — | — | |
| TVAEModel=MLP2026.06 | 5.5 | — | — | |
| CTGANModel=XGB2026.06 | 7.1 | — | — | |
| CTGANModel=MLP2026.06 | 13.7 | — | — | |
| ADAModel=MLP2026.06 | 14.7 | — | — | |
| Offline Random Forest Regression (RFR)Training mode=Offline, Access=Unlimited access to dataset2026.02 | — | 0.01 | 0.669 | |
| Prototype-based generative replay frameworkConfiguration=Best config, Learning mode=Incremental/Online2026.02 | — | 0.014 | 0.553 |