Algorithm 1.

Proposed H-DNN.

Input: Genome data, D, with attributes, a

Output: Decision Tree with classes

1.   tree = { }

2.   minVal = 0

3.   for each a ϵ D do://Considering Input Layer of ANN

4.     for each node n ∈ a and input xn do:

5.      outn = xn//Considering Hidden Layer of ANN

6.     for each hidden node h do:

7.      $ou{t}_h=\sum _n\varnothing (w_{hn}.ou{t}_n)$

8.     g = GiniIndex(outh, d)

9.     for each output node k do:

10.     $ou{t}_k=\sum _k\varnothing (w_{kh}.ou{t}_h)$

11.    Train ANN using Backpropagation(outh)

12.    if g < min Val then

13.    minVal = g

14.    tree′ = {a}

15.  partition(tree, tree′)

16.  repeat till all the partitions are processed

17.  return tree