Table 4.

Four features classification using SVM-GRBF.

Features	C = 1			C = 500			C = 500
	Sigma = 1			Sigma = 1.658			Sigma = 2.658
	10-Fold Cross Validation			10-Fold Cross Validation			10-Fold Cross Validation
	Iterations	Accuracy	Error	Iterations	Accuracy	Error	Iterations	Accuracy	Error
Mean-Std.	13	0.2708	0.4545	81	0.5625	0.3636	578	0.4792	0.4545
Mean-Skew	13	0.8333	0.3636	148	0.9583	0.4545	412	1	0.4545
Mean-Kurt	6	0.7500	0.3636	169	0.8125	0.3636	189	0.5208	0.2727
Std.-Skew	10	0.6042	0.4545	161	0.2083	0.5455	207	0.1875	0.6364
Std.-Kurt	6	0.3750	0.1818	419	0.6875	0.6364	172	0.7083	0.4545
Skew-Kurt	12	0.6875	0	200	0.5833	0.1818	243	0.7292	0.0909
4-Features	11	0.4375	0.3636	38	0.7292	0.4545	86	0.4583	0.4545