Multiclass Classification on cmc
56.6AccuracyMLP
Evaluation results
| Method | Links | ||||
|---|---|---|---|---|---|
| MLPPredictor=MLP, Feature Engineering=LLM-FE2025.03 | 56.6 | — | — | — | |
| TabPFNPredictor=TabPFN, Feature Engineering=LLM-FE2025.03 | 56.6 | — | — | — | |
| TabPFNPredictor=TabPFN, Feature Engineering=Base2025.03 | 56.3 | — | — | — | |
| MLPPredictor=MLP, Feature Engineering=Base2025.03 | 55.9 | — | — | — | |
| CatBoostPredictor=CatBoost, Feature Engineering=LLM-FE2025.03 | 54.8 | — | — | — | |
| SBN2025.07 | 54.7 | 0.018 | 0.004 | — | |
| XGBoostPredictor=XGBoost, Feature Engineering=LLM-FE2025.03 | 53.5 | — | — | — | |
| LLM-FEBackbone=XGBoost, n (number of samples)=1473, p (number of features)=92025.03 | 53.1 | — | — | — | |
| XGBoostPredictor=XGBoost, Feature Engineering=Base2025.03 | 52.8 | — | — | — | |
| BaseBackbone=XGBoost, n (number of samples)=1473, p (number of features)=92025.03 | 52.8 | — | — | — | |
| XGBoost2025.07 | 52.7 | 0.018 | 0.004 | — | |
| Logistic RegressionPredictor=Logistic Regression, Feature Engineering=LLM-FE2025.03 | 52.5 | — | — | — | |
| OCTreeBackbone=XGBoost, n (number of samples)=1473, p (number of features)=92025.03 | 52.5 | — | — | — | |
| CAAFEBackbone=XGBoost, n (number of samples)=1473, p (number of features)=92025.03 | 52.4 | — | — | — | |
| Logistic RegressionPredictor=Logistic Regression, Feature Engineering=Base2025.03 | 52 | — | — | — | |
| CatBoostPredictor=CatBoost, Feature Engineering=Base2025.03 | 51.8 | — | — | — | |
| OpenFEBackbone=XGBoost, n (number of samples)=1473, p (number of features)=92025.03 | 51.7 | — | — | — | |
| AutoFeatBackbone=XGBoost, n (number of samples)=1473, p (number of features)=92025.03 | 50.5 | — | — | — | |
| FeatLLMBackbone=XGBoost, n (number of samples)=1473, p (number of features)=92025.03 | 47.9 | — | — | — | |
| SeBAshot=102026.05 | 46.3 | 0.62 | — | — | |
| D2R2-cshots=52026.05 | 43.39 | — | — | — | |
| D2R2-cshot=52026.05 | 43.39 | 0.37 | — | — | |
| SeBAshots=52026.05 | 42.85 | — | — | — | |
| SeBAshot=52026.05 | 42.85 | 0.62 | — | — | |
| STUNTshot=102026.05 | 42.01 | 5.18 | — | — | |
| D2R2-cshot=12026.05 | 40.81 | 0.41 | — | — | |
| STUNTshots=52026.05 | 40.4 | — | — | — | |
| STUNTshot=52026.05 | 40.4 | 3.55 | — | — | |
| CatBoostshots=52026.05 | 39.89 | — | — | — | |
| VIMEshots=52026.05 | 39.83 | — | — | — | |
| SubTabshots=52026.05 | 39.81 | — | — | — | |
| D2R2-cshot=102026.05 | 38.41 | 0.58 | — | — | |
| TabPFNshots=52026.05 | 38.31 | — | — | — | |
| Scarfshots=52026.05 | 37.75 | — | — | — | |
| MeanTshots=52026.05 | 37.73 | — | — | — | |
| kNNshots=52026.05 | 37.65 | — | — | — | |
| PseudoLshots=52026.05 | 37.49 | — | — | — | |
| T-JEPAshots=52026.05 | 37.25 | — | — | — | |
| STUNTshot=12026.05 | 37.1 | 2.98 | — | — | |
| SeBAshot=12026.05 | 36.76 | 0.72 | — | — | |
| SAINTshots=52026.05 | 35.41 | — | — | — |