Table 6. MLP, RBF neural networks and linear SVM (), SVM with polynomial kernel () and SVM with RBF kernel () classifications using the projections of the features from PCA analysis of the HRV records from normal (N) and cardiovascular risk (R) subjects.

Number of PCA Projections	Classifier	Se (%)	Sp (%)	Np (%)	Pp (%)	Ac (%)
3	MLP	60.00	73.33	64.71	69.23	66.67
	RBFNN	40.00	93.33	60.87	85.71	66.67
	SVM (Linear)	77.27	63.64	73.68	68.00	70.45
	SVM (Polynomial kernel)	84.09	70.45	81.58	74.00	77.27
	SVM (RBF kernel)	89.39	65.15	86.00	71.95	77.27
4	MLP	80.00	80.00	80.00	80.00	80.00
	RBFNN	46.67	86.67	61.90	77.78	66.67
	SVM (Linear)	90.91	90.91	90.91	90.91	90.91
	SVM (Polynomial kernel)	90.91	93.18	91.11	93.02	92.05
	SVM (RBF kernel)	93.94	89.39	93.65	89.86	91.67
5	MLP	66.67	100.00	75.00	100.00	83.33
	RBFNN*	N/A	N/A	N/A	N/A	N/A
	SVM (Linear)	86.36	95.45	87.50	95.00	90.91
	SVM (Polynomial kernel)	81.82	95.45	84.00	94.74	88.64
	SVM (RBF kernel)	81.82	95.45	84.00	94.74	88.64
10	MLP	80.00	73.33	78.57	75.00	76.67
	RBFNN*	N/A	N/A	N/A	N/A	N/A
	SVM (Linear)	81.82	81.82	81.82	81.82	81.82
	SVM (Polynomial kernel)	81.82	95.45	84.00	94.74	88.64
	SVM (RBF kernel)	81.82	95.45	84.00	94.74	88.64

*The results for this classifier were not reported due to their poorness.