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Proposed classification results with 10‐fold validation strategy on dataset 2 using different machine learning algorithms, FNR is representing false negative rate
| Classifier | Accuracy (%) | FNR (%) | Precision (%) | Sensitivity (%) | Time (s) |
|---|---|---|---|---|---|
| LD | 98.7 | 1.3 | 98.78 | 98.20 | 20.00 |
| QSVM | 98.9 | 1.2 | 98.95 | 98.10 | 67.16 |
| LSVM | 98.7 | 1.3 | 98.78 | 97.99 | 73.45 |
| CSVM | 98.9 | 1.1 | 98.94 | 98.20 | 83.31 |
| MGSVM | 97.6 | 2.4 | 97.62 | 97.11 | 121.3 |
| CKNN | 97.5 | 2.5 | 97.65 | 97.09 | 56.94 |
| LR | 98.6 | 1.4 | 98.70 | 97.99 | 417.7 |
