public override void Train(int NumberOfIteration)
{
Random Randomizer = new Random();
ListShuffler Shuffler = new ListShuffler();
Shuffler.Shuffle(Points, Randomizer);
double CurrentError = 0;
foreach (Point TargetPoint in Points)
{
this.SetTargetPoints(TargetPoint);
LambdaParameter = MaxRange * Math.Pow(MinRange / MaxRange, NumberOfIteration / (double)EpochsCount);
Winner = this.SeekForWinner();
NeuronsToChange = this.GetNeuronsToChange();
this.SetNeuronPotential(NumberOfIteration);
CurrentError += Winner.CalculateDistanceFrom(TargetPoint);
this.UpdateWeights(NumberOfIteration, TargetPoint);
}
foreach (Neuron Neuron in Neurons)
{
Neuron.UpdatePositions(Neuron.GetWeight(0), Neuron.GetWeight(1));
}
Errors.Add(new Point(NumberOfIteration, CurrentError / Points.Count()));
}
private List <Neuron> GetNeuronsToChange()
{
List <Neuron> NeuronsToUpdate = new List <Neuron>();
foreach (Neuron Neuron in Neurons)
{
Point NeuronAsPoint = Neuron.GetAsPoint();
if (Winner.CalculateDistanceFrom(NeuronAsPoint) < LambdaParameter)
{
NeuronsToUpdate.Add(Neuron);
}
}
NeuronsToUpdate.Add(Winner);
return(NeuronsToUpdate);
}
