Classification on jungle_chess
96.9AccuracyLLM-FE
Evaluation results
| Method | Links | |
|---|---|---|
| LLM-FEBackbone=XGBoost, n (number of samples)=44.8k, p (number of features)=62025.03 | 96.9 | |
| CAAFEBackbone=XGBoost, n (number of samples)=44.8k, p (number of features)=62025.03 | 90.1 | |
| OpenFEBackbone=XGBoost, n (number of samples)=44.8k, p (number of features)=62025.03 | 90 | |
| BaseBackbone=XGBoost, n (number of samples)=44.8k, p (number of features)=62025.03 | 86.9 | |
| OCTreeBackbone=XGBoost, n (number of samples)=44.8k, p (number of features)=62025.03 | 86.9 | |
| FeatLLMBackbone=XGBoost, n (number of samples)=44.8k, p (number of features)=62025.03 | 57.7 |