Table 6. Performance metrics of the algorithms.
| Accuracy | Precision | Sensitivity | F-Measure | MCC | |
|---|---|---|---|---|---|
| Bagging | 0.8976 | 0.8920 | 0.8980 | 0.8900 | 0.6210 |
| Naive Bayes | 0.7561 | 0.8550 | 0.7560 | 0.7820 | 0.4560 |
| Support Vector Machine | 0.8268 | 0.8570 | 0.8270 | 0.7550 | 0.1840 |
| Boosting (Decision Stump) | 0.8511 | 0.8740 | 0.8510 | 0.8050 | 0.3850 |
| Random Forest | 0.8912 | 0.9000 | 0.8910 | 0.8720 | 0.5900 |
| Nearest Neighbour Classifier | 0.8479 | 0.8320 | 0.8480 | 0.8360 | 0.4220 |
| DO | 0.9588 | 0.9291 | 0.8187 | 0.8704 | 0.8485 |
| ABC | 0.9599 | 0.9178 | 0.8375 | 0.8758 | 0.8532 |
| HHO | 0.9599 | 0.9122 | 0.8438 | 0.8766 | 0.8536 |
| SCA | 0.9578 | 0.8409 | 0.9250 | 0.8810 | 0.8568 |
| FA | 0.9588 | 0.8954 | 0.8562 | 0.8754 | 0.8511 |
| BA | 0.9599 | 0.8315 | 0.9563 | 0.8895 | 0.8683 |
| NI-GWO | 0.9926 | 0.9940 | 0.9938 | 0.9742 | 0.9740 |
| CNI-GWO1 with circle map | 0.9989 | 0.9938 | 1 | 0.9962 | 0.9962 |
| CNI-GWO1 with logistic map | 1 | 1 | 1 | 1 | 1 |
| CNI-GWO1 with iterative map | 1 | 1 | 1 | 1 | 1 |
| CNI-GWO2 with circle map | 1 | 1 | 1 | 1 | 1 |
| CNI-GWO2 with logistic map | 1 | 1 | 1 | 1 | 1 |
| CNI-GWO2 with iterative map | 1 | 1 | 1 | 1 | 1 |
| CNI-GWO3 with circle map | 0.9989 | 0.9938 | 1 | 0.9962 | 0.9962 |
| CNI-GWO3 with logistic map | 1 | 1 | 1 | 1 | 1 |
| CNI-GWO3 with iterative map | 1 | 1 | 1 | 1 | 1 |
| CNI-GWO4 with circle map | 1 | 1 | 1 | 1 | 1 |
| CNI-GWO4 with logistic map | 1 | 1 | 1 | 1 | 1 |
| CNI-GWO4 with iterative map | 1 | 1 | 1 | 1 | 1 |