Classification on electricity
0.0665Mean Test Error RateOCTree
Evaluation results
| Method | Links | ||||||
|---|---|---|---|---|---|---|---|
| OCTreePrediction model=XGBoost2024.06 | 0.0665 | 20.1 | — | — | — | — | |
| ELLMScenario=Joint FE + HPO, Downstream Model=XGBoost2026.02 | 0.0679 | — | — | — | — | — | |
| CoFEHScenario=Joint FE + HPO, Downstream Model=XGBoost2026.02 | 0.0715 | — | — | — | — | — | |
| CoFEHScenario=Standalone FE, Downstream Model=XGBoost2026.02 | 0.0731 | — | — | — | — | — | |
| LFGScenario=Joint FE + HPO, Downstream Model=XGBoost2026.02 | 0.0765 | — | — | — | — | — | |
| ELLMScenario=Standalone FE, Downstream Model=XGBoost2026.02 | 0.0771 | — | — | — | — | — | |
| OCTreeScenario=Joint FE + HPO, Downstream Model=XGBoost2026.02 | 0.0776 | — | — | — | — | — | |
| OpenFEScenario=Joint FE + HPO, Downstream Model=XGBoost2026.02 | 0.0793 | — | — | — | — | — | |
| MindwareScenario=Joint FE + HPO, Downstream Model=XGBoost2026.02 | 0.0828 | — | — | — | — | — | |
| BaselinePrediction model=XGBoost2024.06 | 0.0832 | — | — | — | — | — | |
| OpenFEScenario=Standalone FE, Downstream Model=XGBoost2026.02 | 0.0847 | — | — | — | — | — | |
| OCTreeScenario=Standalone FE, Downstream Model=XGBoost2026.02 | 0.0854 | — | — | — | — | — | |
| LFGScenario=Standalone FE, Downstream Model=XGBoost2026.02 | 0.0884 | — | — | — | — | — | |
| MindwareScenario=Standalone FE, Downstream Model=XGBoost2026.02 | 0.0908 | — | — | — | — | — | |
| EPIC-IIIMethod Category=Prompt-based2025.12 | 0.115 | — | 14.42 | 564 | — | — | |
| DATEMethod Category=Our Method2025.12 | 0.1278 | — | 4.93 | 139 | — | — | |
| DATE-IMethod Category=Our Method2025.12 | 0.131 | — | 2.52 | 56 | — | — | |
| GReaT-IIIMethod Category=Fine-tuning based2025.12 | 0.1357 | — | -0.97 | 1,000 | — | — | |
| CLLMMethod Category=Prompt-based2025.12 | 0.1357 | — | -1.02 | 1,000 | — | — | |
| CTGANMethod Category=GAN-based2025.12 | 0.143 | — | -6.39 | 10,000 | — | — | |
| GReaT-VMethod Category=Fine-tuning based2025.12 | 0.1454 | — | -8.22 | 1,000 | — | — | |
| OCTreePrediction model=HyperFast2024.06 | 0.147 | 3.6 | — | — | — | — | |
| OCTreePrediction model=MLP2024.06 | 0.1482 | 5.2 | — | — | — | — | |
| EPIC-IIMethod Category=Prompt-based2025.12 | 0.15 | — | -11.63 | 300 | — | — | |
| BaselinePrediction model=HyperFast2024.06 | 0.1525 | — | — | — | — | — | |
| BaselinePrediction model=MLP2024.06 | 0.1564 | — | — | — | — | — | |
| EPIC-IMethod Category=Prompt-based2025.12 | 0.2255 | — | -67.8 | 1,195 | — | — | |
| CCFEvaluation protocol=CV splits2025.12 | — | — | — | — | 0.703 | — | |
| H1setting=HardCOp4DA, augmentation=Saug, heuristic=Mean152026.05 | — | — | — | — | — | 76.1 | |
| H2setting=HardCOp4DA, augmentation=Saug, heuristic=Ensem202026.05 | — | — | — | — | — | 75.9 | |
| H3setting=HardCOp4DA, augmentation=Saug, heuristic=XXL2026.05 | — | — | — | — | — | 76 | |
| JARFEvaluation protocol=CV splits2025.12 | — | — | — | — | 0.78 | — | |
| KANFLOPs=2992, Param=7202025.06 | — | — | — | — | — | 79.62 | |
| LDA+RFEvaluation protocol=CV splits2025.12 | — | — | — | — | 0.659 | — | |
| MLPFLOPs=544, Param=2982025.06 | — | — | — | — | — | 77.62 | |
| NS-SRFLOPs=1056, Param=5542025.06 | — | — | — | — | — | 79.32 | |
| NS-TDFLOPs=1568, Param=8102025.06 | — | — | — | — | — | 78.62 | |
| O1setting=HardCOp4DA, augmentation=Saug, heuristic=Kmeans2026.05 | — | — | — | — | — | 76.9 | |
| O2setting=HardCOp4DA, augmentation=Saug, heuristic=DT+TFM2026.05 | — | — | — | — | — | 84.7 | |
| PCA+RFEvaluation protocol=CV splits2025.12 | — | — | — | — | 0.654 | — | |
| RFEvaluation protocol=CV splits2025.12 | — | — | — | — | 0.664 | — | |
| RotFEvaluation protocol=CV splits2025.12 | — | — | — | — | 0.65 | — | |
| SPORFEvaluation protocol=CV splits2025.12 | — | — | — | — | 0.689 | — | |
| VIP-COPsetting=HardCOp4DA, augmentation=Saug2026.05 | — | — | — | — | — | 77.4 | |
| XGBEvaluation protocol=CV splits2025.12 | — | — | — | — | 0.685 | — |