MLCQ God Class XGBoost Evaluation Approaches
Comparison Table
| Approach |
Accuracy |
Precision |
Recall |
F1-score |
| Token Based |
0.8185 |
0.6119 |
0.4525 |
0.5152 |
| Tree Based |
0.7826 |
0.4936 |
0.4877 |
0.4865 |
| Metric Based |
0.8138 |
0.5619 |
0.5881 |
0.5723 |
| PreTrained |
0.7952 |
0.5153 |
0.6022 |
0.5537 |
Bar Plot
Evaluation Results
XGBoost - Token Based
- Accuracy: 0.8185
- Precision: 0.6119
- Recall: 0.4525
- F1-score: 0.5152
XGBoost - Tree Based
- Accuracy: 0.7826
- Precision: 0.4936
- Recall: 0.4877
- F1-score: 0.4865
XGBoost - Metric Based
- Accuracy: 0.8138
- Precision: 0.5619
- Recall: 0.5881
- F1-score: 0.5723
XGBoost - PreTrained
- Accuracy: 0.7952
- Precision: 0.5153
- Recall: 0.6022
- F1-score: 0.5537
