Table 4.
Features | Classifiers | Evaluation metrics | Delta | Theta | Alpha | Beta |
---|---|---|---|---|---|---|
PDC features | KNN | Sensitivity | 93.52 ± 0.61 | 98.31 ± 0.52 | 98.85 ± 0.83 | 91.32 ± 2.23 |
Specificity | 92.82 ± 1.77 | 95.91 ± 4.01 | 94.32 ± 0.79 | 87.82 ± 0.79 | ||
Accuracy | 75.00 ± 4.40 | 70.83 ± 2.67 | 76.54 ± 2.76 | 74.37 ± 3.58 | ||
LDA | Sensitivity | 94.83 ± 1.75 | 95.66 ± 1.044 | 99.32 ± 1.38 | 96.83 ± 0.75 | |
Specificity | 93.00 ± 4.44 | 93.62 ± 3.56 | 97.87 ± 3.46 | 94.61 ± 2.49 | ||
Accuracy | 67.00 ± 7.71 | 62.83 ± 7.26 | 68.08 ± 6.59 | 66.58 ± 7.39 | ||
NB | Sensitivity | 97.18 ± 1.87 | 97.12 ± 1.0 | 85.71 ± 16.07 | 92.15 ± 2.32 | |
Specificity | 96.28 ± 2.17 | 96.33 ± 3.01 | 85.18 ± 1.51 | 94.23 ± 0.77 | ||
Accuracy | 79.70 ± 2.52 | 71.47 ± 2.07 | 79.75 ± 1.91 | 87.10 ± 2.11 | ||
DT | Sensitivity | 92.71 ± 7.10 | 89.30 ± 9.23 | 93.91 ± 11.12 | 91.80 ± 0.86 | |
Specificity | 91.28 ± 6.20 | 81.84 ± 8.09 | 91.14 ± 4.51 | 92.82 ± 5.31 | ||
Accuracy | 75.95 ± 4.15 | 72.12 ± 3.68 | 75.62 ± 2.24 | 75.00 ± 2.74 | ||
SVM | Sensitivity | 91.27 ± 6.20 | 94.27 ± 6.13 | 93.25 ± 4.27 | 91.53 ± 6.47 | |
Specificity | 90.13 ± 6.81 | 93.23 ± 6.81 | 92.12 ± 5.91 | 90.19 ± 9.28 | ||
Accuracy | 79.29 ± 5.93 | 83.66 ± 6.72 | 82.79 ± 7.86 | 80.08 ± 10.94 |