Table 3: Kernel optimization for support vector machine.
Kernel types |
Performance measures |
||
Accuracy (%) |
Sensitivity (%) |
Specificity (%) |
|
Linear |
64.26 |
64.88 |
51.18 |
RBF |
65.61 |
66.27 |
52.28 |
Polynomial-2 |
64.36 |
64.96 |
43.15 |
Sigmoid |
58.58 |
59.35 |
51.57 |
Laplace |
64.67 |
65.34 |
52.28 |
RBF: Radial Basis Function