public TNeuralData(TNeuralData Data)
{
this.mqxB9tafd = Data.mqxB9tafd;
this.XkLVodNhF = Data.mqxB9tafd;
this.dRXrjBaeW = this.mqxB9tafd == 0 ? (double[]) null : new double[this.mqxB9tafd];
this.s9P8N17Q3 = this.XkLVodNhF == 0 ? (double[]) null : new double[this.XkLVodNhF];
for (int index = 0; index < this.mqxB9tafd; ++index)
this.dRXrjBaeW[index] = Data.dRXrjBaeW[index];
for (int index = 0; index < this.XkLVodNhF; ++index)
this.s9P8N17Q3[index] = Data.s9P8N17Q3[index];
}
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 Renormalize()
{
for (int Col = 0; Col < this.fNInput; ++Col)
{
double storedMean = this.GetStoredMean(Col);
double num1 = Math.Sqrt(this.GetStoredVariance(Col));
for (int Seek = 0; Seek < this.fData.Count; ++Seek)
{
TNeuralData data = this.GetData(Seek);
double num2 = data.Input[Col];
data.Input[Col] = num2 * num1 + storedMean;
}
}
}
public TNeuralData(TNeuralData Data)
{
this.mqxB9tafd = Data.mqxB9tafd;
this.XkLVodNhF = Data.mqxB9tafd;
this.dRXrjBaeW = this.mqxB9tafd == 0 ? (double[])null : new double[this.mqxB9tafd];
this.s9P8N17Q3 = this.XkLVodNhF == 0 ? (double[])null : new double[this.XkLVodNhF];
for (int index = 0; index < this.mqxB9tafd; ++index)
{
this.dRXrjBaeW[index] = Data.dRXrjBaeW[index];
}
for (int index = 0; index < this.XkLVodNhF; ++index)
{
this.s9P8N17Q3[index] = Data.s9P8N17Q3[index];
}
}
public void PrintTrainingSetError()
{
int ndata = this.tD5M1LlFx.GetNData();
double num = 0.0;
for (int Seek = 0; Seek < ndata; ++Seek)
{
TNeuralData data = this.tD5M1LlFx.GetData(Seek);
this.fInput = data.Input;
this.fTarget = data.Output;
this.FeedForward();
this.ComputeError();
num += this.GetError();
this.PrintError();
}
}
public double GetTrainingSetError(int Option)
{
if (Option != 0)
{
return(this.wm8s050QY);
}
int ndata = this.tD5M1LlFx.GetNData();
double num = 0.0;
for (int Seek = 0; Seek < ndata; ++Seek)
{
TNeuralData data = this.tD5M1LlFx.GetData(Seek);
this.fInput = data.Input;
this.fTarget = data.Output;
this.FeedForward();
this.ComputeError();
num += this.GetError();
}
return(num / (double)ndata);
}
public double GetValidationSetError(int Option)
{
if (Option != 0)
{
return(this.MSg9cpEpW);
}
if (this.WKl1lduPx == null)
{
return(0.0);
}
int ndata = this.WKl1lduPx.GetNData();
double num = 0.0;
for (int Seek = 0; Seek < ndata; ++Seek)
{
TNeuralData data = this.WKl1lduPx.GetData(Seek);
this.fInput = data.Input;
this.fTarget = data.Output;
this.FeedForward();
this.ComputeError();
num += this.GetError();
}
return(num / (double)ndata);
}
public void AddData(TNeuralData NeuralData)
{
this.fData.Add((object) NeuralData);
++this.fNData;
}
public void AddData(TNeuralData NeuralData)
{
this.fData.Add((object)NeuralData);
++this.fNData;
}
