public List<double> RunMlpSingle(Sample sample)
{
List<double> output = Hidden.RunLayerSingle(sample);
var outputAsSample = new Sample();
outputAsSample.Inputs = output;
return Last.RunLayerSingle(outputAsSample);
}
public void TrainMlp(
List<Sample> samples,
List<double> expectedAnswers,
double maxError,
int maxEpochs)
{
var error = double.MaxValue;
var epoch = 0;
while (epoch < maxEpochs && error > maxError)
{
epoch++;
error = 0;
var errors = new List<double>();
for (int k = 0; k < samples.Count; k++)
{
RunMlpSingle(samples[k]);
var sampleFromHiddenOtput = new Sample();
sampleFromHiddenOtput.Inputs = Hidden.Neurons.Select(x => x.YValue).ToList();
errors = Last.TrainLastSingle(sampleFromHiddenOtput, expectedAnswers[k]);
Hidden.TrainHiddenSingle(samples[k], Last);
foreach (var e in errors)
{
error += Math.Pow(e, 2);
}
}
error = error / (samples.Count * errors.Count);
}
Console.WriteLine("Epochs used: " + epoch);
}