Table 5. MLP, RBF neural networks and linear SVM (), SVM with polynomial kernel () and SVM with RBF kernel () classifications using classical and non-linear/multi-resolution features of the HRV records from normal (N) and cardiovascular risk (R) subjects.

Features	Classifier	Se (%)	Sp (%)	Np (%)	Pp (%)	Ac (%)
Statistical + Spectral	MLP	66.67	60.00	64.29	62.50	63.33
	RBFNN	26.67	93.33	56.00	80.00	60.00
	SVM (Linear)	72.73	86.36	76.00	84.21	79.55
	SVM (Polynomial kernel)	68.18	70.45	68.89	69.77	69.32
	SVM (RBF kernel)	68.18	74.24	70.00	72.58	71.21
Non-linear + Multi-resolution	MLP	80.00	100.00	83.33	100.00	90.00
	RBFNN	73.33	100.00	78.95	100.00	86.67
	SVM (Linear)	95.45	77.27	94.44	80.77	86.36
	SVM (Polynomial kernel)	88.64	81.82	87.80	82.98	85.23
	SVM (RBF kernel)	90.91	83.33	90.16	84.51	87.12