public static neuralnet cross(neuralnet a, neuralnet b, int nr_cat)
{
neuralnet aux = new neuralnet(a);
int piv = (a.layers.Count + b.layers.Count) / (2 * nr_cat);
for (int i = piv; i < b.size; i++)
{
if (i > aux.size)
{
aux.layers.Add(new layer());
}
aux.layers[i].schimba(b.layers[i]);
}
foreach (node n in aux.layers[piv].nodes)
{
while (n.conexiuni.Count > aux.layers[piv - 1].size)
{
n.conexiuni.RemoveAt(n.conexiuni.Count);
}
while (n.conexiuni.Count < aux.layers[piv - 1].size)
{
n.conexiuni.Add(Random.Range(-100f, 100f));
}
}
return(aux);
}
public neuralnet(neuralnet n)
{
this.input_size = n.input_size;
this.layers = n.layers;
this.size = n.size;
}
