Table 5.

Area of ROC (AUC %) on the k-fold using support vector machine (SVM) models with kernels and parameters (Class A features as input).

Kernels	R	AUC
RBF $\sigma =1$	0.2	93.44
	1	95.08
	10	95.31
RBF $\sigma =5$	0.2	92.86
	1	94.57
	10	95.03
RBF $\sigma =25$	0.2	83.38
	1	88.34
	10	94.09
Poly d = 2	0.2	94.86
	1	94.86
	10	94.99
Poly d = 3	0.2	95.02
	1	94.78
	10	95.18
Poly d = 4	0.2	95.53
	1	95.42
	10	94.71
Linear	0.2	94.80
	1	95.23
	10	94.66