public double Evaluate(PlacementPackage placement)
{
placement.Normalize();
double[] intermediateScores = new double[Hidden + 1];
//for (int iIntermediateScore = 0; iIntermediateScore < intermediateScores.Length - 1; iIntermediateScore++) {
// intermediateScores[iIntermediateScore] = 0;
//}
intermediateScores[intermediateScores.Length - 1] = 1;
for (int iInput = 0; iInput <= Input; iInput++) // the last gotten feature is the input bias
{
double feature = placement.GetFeature(iInput);
int index = iInput * Hidden;
for (int iHidden = 0; iHidden < Hidden; iHidden++)
{
intermediateScores[iHidden] += feature * Weights[index + iHidden];
}
}
for (int inter = 0; inter < intermediateScores.Length - 1; inter++)
{
if (intermediateScores[inter] < 0)
{
intermediateScores[inter] = 0;
}
}
double result = 0;
int outputIndex = (this.Input + 1) * this.Hidden;
for (int inter = 0; inter < intermediateScores.Length; inter++)
{
double temp = intermediateScores[inter] * Weights[outputIndex + inter];
result += temp;
}
result = 1 / (1 + Math.Pow(Math.E, -result));
return(result);
//double result = 0;
//for (int i = 0; i < ANNSettings.Input; i++) {
// result += placement.GetFeature(i) * Weights[i];
//}
//return result;
}
