TABLE 3.
The classification performance of the SVM classifier uses the leave-one-sample-out 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 | 89.47 | 92.85 | 80.00 | 92.85 | 92.85 | 73.68 | 100.00 | 0.00 | 84.85 | 78.57 | 73.68 | 100.00 | 0.00 | 84.85 | 35.71 |
| 0.1 | 84.21 | 85.72 | 80.00 | 88.89 | 94.28 | 73.68 | 100.00 | 0.00 | 84.85 | 77.14 | 73.68 | 100.00 | 0.00 | 84.85 | 35.71 | |
| 1 | 94.73 | 92.85 | 100 | 96.29 | 94.28 | 63.15 | 85.71 | 0.00 | 77.42 | 82.85 | 68.42 | 85.71 | 20.00 | 80.00 | 41.43 | |
| 10 | 89.47 | 92.85 | 80.00 | 92.85 | 92.85 | 84.21 | 85.71 | 80.00 | 88.89 | 92.85 | 63.15 | 78.57 | 20.00 | 75.86 | 27.14 | |
| 100 | 89.47 | 92.85 | 80.00 | 92.85 | 77.14 | 84.21 | 85.71 | 80.00 | 88.89 | 92.85 | 52.63 | 64.28 | 20.00 | 66.67 | 20.00 | |
| RBF | 0.01 | 73.68 | 100.00 | 0.00 | 84.84 | 82.85 | 73.68 | 100.00 | 0.00 | 84.85 | 78.57 | 73.68 | 100.00 | 0.00 | 84.85 | 41.43 |
| 0.1 | 73.68 | 100.00 | 0.00 | 84.84 | 82.85 | 73.68 | 100.00 | 0.00 | 84.85 | 80.00 | 73.68 | 100.00 | 0.00 | 84.85 | 42.85 | |
| 1 | 84.21 | 92.85 | 60.00 | 89.65 | 84.28 | 73.68 | 100.00 | 0.00 | 84.85 | 80.00 | 73.68 | 100.00 | 0.00 | 84.85 | 42.85 | |
| 10 | 84.21 | 92.85 | 60.00 | 89.65 | 72.85 | 63.15 | 85.71 | 0.00 | 77.42 | 87.14 | 63.15 | 78.57 | 20.00 | 75.86 | 48.57 | |
| 100 | 68.42 | 78.57 | 40.00 | 78.57 | 74.28 | 84.21 | 85.71 | 80.00 | 88.89 | 92.85 | 63.15 | 78.57 | 20.00 | 75.86 | 48.57 | |
| Polynomial | 0.01 | 89.47 | 92.85 | 80.00 | 92.85 | 77.14 | 73.68 | 100.00 | 0.00 | 84.85 | 84.28 | 73.68 | 100.00 | 0.00 | 84.85 | 40.00 |
| 0.1 | 89.47 | 92.85 | 80.00 | 92.85 | 74.28 | 73.68 | 100.00 | 0.00 | 84.85 | 74.28 | 68.42 | 92.85 | 0.00 | 81.25 | 41.42 | |
| 1 | 89.47 | 92.85 | 80.00 | 92.85 | 71.43 | 73.68 | 100.00 | 0.00 | 84.85 | 77.14 | 63.15 | 78.57 | 20.00 | 75.86 | 42.85 | |
| 10 | 84.21 | 85.71 | 80.00 | 88.89 | 87.14 | 68.42 | 92.85 | 0.00 | 81.25 | 75.71 | 52.63 | 57.14 | 40.00 | 64.00 | 27.14 | |
| 100 | 84.21 | 85.71 | 80.00 | 88.89 | 88.57 | 78.94 | 85.71 | 60.00 | 85.71 | 92.85 | 42.10 | 42.85 | 40.00 | 52.17 | 25.71 | |
The results reported are for the three spectral features. Best performance is obtained with the spectral feature using the linear kernel (C ): 94.73% Accuracy, 92.85% Sensitivity, 100% Specificity, 96.29% F1-score. (ACC, accuracy; SENS, sensitivity; SPEC, specificity; F1, F1-score; AUC, AREA UNDER the ROC CURVE).
Bold values represent the best performance.