public void TrainPerceptron()
{
this.x1tDaZE2v = false;
int num1 = 0;
int num2 = 0;
int num3 = 0;
label_1:
do
{
do
{
for (int index = 0; index < this.fNBatch; ++index)
{
TNeuralData data = this.tD5M1LlFx.GetData();
this.fInput = data.Input;
this.fTarget = data.Output;
this.FeedForward();
this.ComputeError();
this.FeedBackward();
}
this.Update(0);
TPerceptron tperceptron = this;
int num4 = tperceptron.fNPattern + this.fNBatch;
tperceptron.fNPattern = num4;
num1 += this.fNBatch;
num2 += this.fNBatch;
if (this.x1tDaZE2v)
{
Console.WriteLine("");
return;
}
else if (this.fSMethod == EStoppingMethod.PatternNumber && (double)num1 >= this.fSParameter)
{
Console.WriteLine("", this.fSParameter);
return;
}
}while (num2 < this.fNGraphUpdate);
num2 = 0;
this.wm8s050QY = this.GetTrainingSetError();
this.V8laR9xb7.Add((double)num3, this.wm8s050QY);
if (this.WKl1lduPx != null)
{
this.MSg9cpEpW = this.GetValidationSetError();
this.XOwvCEen2.Add((double)num3, this.MSg9cpEpW);
}
++num3;
}while (this.fViewMode != EViewMode.OnLine);
goto label_1;
}
public void AddHiddenLayer(int NHidden)
{
TNeuralLayer Layer1 = (TNeuralLayer)this.rCHgEckPw[this.rCHgEckPw.Count - 1];
TNeuralLayer Layer2 = (TNeuralLayer) new THiddenNeuralLayer(NHidden);
this.fOutputLayer.Disconnect(Layer1);
this.fOutputLayer.Connect(Layer2);
Layer2.Connect(Layer1);
this.rCHgEckPw.Add((object)Layer2);
++this.HnCyxyTcM;
this.kB5uny9D9 += NHidden;
this.fMaxNX = Math.Max(this.fMaxNX, NHidden + 1);
TPerceptron tperceptron = this;
int num = tperceptron.fMaxNY + 1;
tperceptron.fMaxNY = num;
}
