Table 6.
Performance metrics of the models.
| Models | Groups | Sensitivity (%) | Specificity (%) | Precision (%) | F1 score (%) | Accuracy (%) | Class. Error | Kappa |
|---|---|---|---|---|---|---|---|---|
| Gradient Boosted Trees (GBTs) | Mild | 96.97 | 97.98 | 94.12 | 95.52 | 96.98 | 3.02 | 0.96 |
| Severe | 1.00 | 98.99 | 97.06 | 98.51 | ||||
| Critical | 90.91 | 98.99 | 96.77 | 93.75 | ||||
| Control | 1.00 | 1.00 | 1.00 | 1.00 | ||||
| Random Forest (RF) | Mild | 96.97 | 98.99 | 96.97 | 96.97 | 96.21 | 3.79 | 0.95 |
| Severe | 1.00 | 97.98 | 94.29 | 97.06 | ||||
| Critical | 87.88 | 98.99 | 96.67 | 92.06 | ||||
| Control | 1.00 | 98.99 | 97.06 | 98.51 | ||||
| Deep Learning (DL) | Mild | 96.97 | 96.97 | 91.43 | 94.12 | 94.73 | 5.27 | 0.93 |
| Severe | 1.00 | 97.98 | 94.29 | 97.06 | ||||
| Critical | 87.88 | 97.98 | 93.55 | 90.62 | ||||
| Control | 93.94 | 1.00 | 1.00 | 96.88 |