Table 6.

An example of the algorithm used to determine the prediction value for tree 7.9

a[7.9] : = 4 * RNANet : –Classify (〈1, 1, 1, 3〉);		a[7.9] : = 〈0.95945, 3.52754〉
b[7.9] : = 2 * RNANet : –Classify (〈1, 0, 1, 2〉);		b[7.9] : = 〈0.00030, 1.99985〉
c[7.9] : = 1 * RNANet : –Classify (〈1, 1, 2, 2〉);		c[7.9] : = 〈0.97666, 0.02253〉
d[7.9] : = 4 * RNANet : –Classify (〈1, 1, 2, 1〉);		d[7.9] : = 〈3.95652, 0.05185〉
e[7.9] : = 6 * RNANet : –Classify (〈1, 1, 1, 3〉);		e[7.9] : = 〈1.43917, 5.29130〉
		Class[7.9] := 〈0.43130, 0.64077〉