TABLE 5.
The classification performance of the SVM classifier uses the stratified five-fold cross-validation method with different kernels (linear, Gaussian RBF, and polynomial) for different regularization parameters (C).
| Parameters | Spectral feature | Histogram-Poincaré based feature | Wavelet-based feature | |||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Kernel | C | ACC | SENS | SPEC | F1 | AUC | ACC | SENS | SPEC | F1 | AUC | ACC | SENS | SPEC | F1 | AUC |
| Linear | 0.01 | 90.00 | 93.33 | 80.00 | 93.14 | 80.00 | 73.33 | 100.00 | 0.00 | 84.57 | 83.33 | 73.33 | 100.00 | 0.00 | 84.57 | 33.33 |
| 0.1 | 83.33 | 83.33 | 80.00 | 86.47 | 80.00 | 73.33 | 100.00 | 0.00 | 84.57 | 83.33 | 73.33 | 100.00 | 0.00 | 84.57 | 33.33 | |
| 1 | 95.00 | 93.33 | 100.00 | 96.00 | 80.00 | 73.33 | 83.33 | 40.00 | 80.76 | 83.33 | 75.00 | 93.33 | 20.00 | 84.76 | 33.33 | |
| 10 | 90.00 | 93.33 | 80.00 | 93.14 | 80.00 | 78.33 | 70.00 | 100.00 | 79.33 | 83.33 | 65.00 | 80.00 | 20.00 | 75.62 | 26.67 | |
| 100 | 90.00 | 93.33 | 80.00 | 93.14 | 80.00 | 83.33 | 76.67 | 100.00 | 85.33 | 83.33 | 60.00 | 73.33 | 20.00 | 70.28 | 26.67 | |
| RBF | 0.01 | 73.33 | 100.00 | 0.00 | 84.57 | 80.00 | 73.33 | 100.00 | 0.00 | 84.57 | 90.00 | 73.33 | 100.00 | 0.00 | 84.57 | 46.67 |
| 0.1 | 73.33 | 100.00 | 0.00 | 84.57 | 80.00 | 73.33 | 100.00 | 0.00 | 84.57 | 90.00 | 73.33 | 100.00 | 0.00 | 84.57 | 53.33 | |
| 1 | 85.00 | 93.33 | 60.00 | 90.28 | 80.00 | 73.33 | 100.00 | 0.00 | 84.57 | 90.00 | 68.33 | 93.33 | 0.00 | 80.76 | 53.33 | |
| 10 | 85.00 | 93.33 | 60.00 | 90.28 | 53.33 | 78.33 | 90.00 | 40.00 | 84.76 | 90.00 | 56.67 | 70.00 | 20.00 | 67.62 | 50.00 | |
| 100 | 71.67 | 73.33 | 60.00 | 70.28 | 53.33 | 88.33 | 83.33 | 100.00 | 89.33 | 73.33 | 56.67 | 70.00 | 20.00 | 67.62 | 50.00 | |
| Polynomial | 0.01 | 90.00 | 93.33 | 80.00 | 93.14 | 80.00 | 73.33 | 100.00 | 0.00 | 84.57 | 76.67 | 73.33 | 100.00 | 0.00 | 84.57 | 33.33 |
| 0.1 | 90.00 | 93.33 | 80.00 | 93.14 | 80.00 | 73.33 | 100.00 | 0.00 | 84.57 | 83.33 | 68.33 | 93.33 | 0.00 | 80.76 | 40.00 | |
| 1 | 90.00 | 93.33 | 80.00 | 93.14 | 80.00 | 73.33 | 100.00 | 0.00 | 84.57 | 90.00 | 70.00 | 86.67 | 20.00 | 80.95 | 33.33 | |
| 10 | 90.00 | 93.33 | 80.00 | 93.14 | 80.00 | 73.33 | 100.00 | 0.00 | 84.57 | 90.00 | 60.00 | 66.67 | 40.00 | 68.47 | 13.33 | |
| 100 | 90.00 | 93.33 | 80.00 | 93.14 | 80.00 | 78.33 | 83.33 | 60.00 | 83.62 | 83.33 | 53.33 | 66.67 | 20.00 | 64.47 | 13.33 | |
The results reported are for the three spectral features. Best performance is obtained with spectral feature in linear kernel (C ): 95% Accuracy, 93.33% Sensitivity, 100% Specificity, 96% F1-score.
Bold value represents the best performance.