Table 6 An example of the algorithm used to determine the prediction value for tree 7.9
From: A predictive model for secondary RNA structure using graph theory and a neural network
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〉 |
