Regression on wine 10^0 scaling (five-fold cross-validation)
0.612RMSELLM-FE
Evaluation results
| Method | Links | |
|---|---|---|
| LLM-FEFeature Engineering=LLM-FE, Predictive Model=XGBoost2025.03 | 0.612 | |
| OpenFEFeature Engineering=Classical FE, Predictive Model=XGBoost2025.03 | 0.631 | |
| AutoFeatFeature Engineering=Classical FE, Predictive Model=XGBoost2025.03 | 0.633 | |
| BaseFeature Engineering=None (Base), Predictive Model=XGBoost2025.03 | 0.639 | |
| Base LLMFeature Engineering=LLM-based FE, Predictive Model=XGBoost2025.03 | 0.639 | |
| OCTreeFeature Engineering=LLM-based FE, Predictive Model=XGBoost2025.03 | 0.639 |