Table 5.
Comparison of common classifiers with the proposed LMPL classifier in Experiment 2: COVID-19, SARS, and MERS pneumonia.
| Method | Performance Metrics (%) |
||||
|---|---|---|---|---|---|
| Sensitivity (Recall) | Precision (PPV) | F1-score | Accuracy | Average Rank | |
| NaiveBayes | 89.20 (12) | 94.23 (10) | 91.25 (12) | 92.58 (12) | 11.5 |
| NN ( = 3) | 96.08 (2) | 95.43 (4) | 95.72 (3) | 96.29 (3) | 3.0 |
| NN ( = 5) | 95.31 (5) | 94.95 (6) | 95.08 (6) | 95.72 (5) | 5.3 |
| NN ( = 7) | 94.35 (8) | 94.57 (9) | 94.42 (8) | 95.15 (8) | 8.3 |
| OvO SVM | 94.64 (7) | 93.10 (11) | 93.84 (9) | 95.01 (9) | 9.0 |
| OvA SVM | 95.86 (4) | 94.73 (7) | 95.28 (4) | 96.01 (4) | 4.8 |
| Decision Tree | 94.95 (6) | 95.20 (5) | 95.06 (7) | 95.72 (5) | 5.8 |
| AdaBoostM2 | 93.07 (10) | 94.66 (8) | 93.82 (10) | 94.58 (10) | 9.5 |
| TotalBoost | 93.63 (9) | 96.83 (1) | 95.13 (5) | 95.72 (5) | 5.0 |
| Random Forrest | 96.03 (3) | 95.86 (3) | 95.93 (2) | 96.58 (2) | 2.5 |
| SoftMax | 92.32 (11) | 92.58 (12) | 92.45 (11) | 93.30 (11) | 11.3 |
| Proposed LMPL | 96.64 (1) | 96.29 (2) | 96.46 (1) | 96.86 (1) | 1.3 |
*Bold numbers indicate the best performance.