Table 3 Comparative analysis of the performance outcomes across various machine learning models
Model | F1 score (%) | Accuracy (%) | Recall (%) | Precision (%) | AUC (%) | Sensitivity (%) | Specificity (%) |
|---|---|---|---|---|---|---|---|
LR model | 80.8 | 84.7 | 80.0 | 81.6 | 89.6 | 80.0 | 87.8 |
RF model | 78.5 | 81.5 | 84.0 | 73.7 | 91.6 | 84.0 | 79.7 |
XGBoost model | 81.1 | 83.9 | 86.0 | 76.8 | 88.5 | 86.0 | 82.4 |
LightGBM model | 79.6 | 82.3 | 86.0 | 74.1 | 91.2 | 86.0 | 79.7 |
SVM model | 78.0 | 82.3 | 78.0 | 78.0 | 87.0 | 78.0 | 85.1 |