Table 4.
Comparison of commom classifiers with the proposed LMPL classifier in Experiment 1: Normal, COVID-19, and typical viral pneumonia.
| Method | Performance Metrics (%) |
||||
|---|---|---|---|---|---|
| Sensitivity (Recall) | Precision (PPV) | F1-score | Accuracy | Average Rank | |
| NaiveBayes | 97.94 (12) | 97.63 (12) | 97.78 (12) | 97.75 (12) | 12.0 |
| NN ( = 3) | 98.61 (6) | 98.72 (6) | 98.67 (6) | 98.55 (6) | 6.0 |
| NN (= 5) | 98.53 (7) | 98.75 (5) | 98.64 (7) | 98.52 (8) | 6.8 |
| NN ( = 7) | 98.44 (8) | 98.60 (8) | 98.52 (8) | 98.39 (9) | 8.3 |
| OvO SVM | 98.42 (10) | 98.52 (10) | 98.47 (10) | 98.30 (10) | 10.0 |
| OvA SVM | 98.82 (3) | 98.61 (7) | 98.71 (5) | 98.68 (4) | 4.8 |
| Decision Tree | 98.45 (9) | 98.56 (9) | 98.50 (9) | 98.55 (6) | 8.3 |
| AdaBoostM2 | 98.63 (5) | 98.96 (4) | 98.80 (4) | 98.65 (5) | 4.5 |
| TotalBoost | 98.68 (4) | 99.06 (3) | 98.87 (3) | 98.78 (3) | 3.3 |
| Random Forrest | 98.84 (2) | 99.00 (2) | 98.92 (2) | 98.84 (1) | 1.8 |
| SoftMax | 98.21 (11) | 98.43 (11) | 98.32 (11) | 98.10 (11) | 11.0 |
| Proposed LMPL | 98.87 (1) | 99.08 (1) | 98.97 (1) | 98.81 (2) | 1.3 |
*Bold numbers indicate the best performance.