public static void Train(params string[] args)
{
Parameter parameters = default(Parameter);
Problem problem = default(Problem);
bool flag = default(bool);
int nrfold = default(int);
string filename = default(string);
Training.parseCommandLine(args, out parameters, out problem, out flag, out nrfold, out filename);
if (flag)
{
Training.PerformCrossValidation(problem, parameters, nrfold);
}
else
{
Model.Write(filename, Training.Train(problem, parameters));
}
}
public static RegressionParameter[] GridRegression(Problem problem, Parameter parameters, List <double> CValues, List <double> GammaValues, List <double> PValues, string outputFile, int nrfold, int MaxBestCount)
{
if (!string.IsNullOrEmpty(outputFile))
{
File.WriteAllText(outputFile, string.Empty);
}
List <RegressionParameter> list = new List <RegressionParameter>(CValues.Count * GammaValues.Count * PValues.Count);
for (int i = 0; i < CValues.Count; i++)
{
for (int j = 0; j < GammaValues.Count; j++)
{
for (int k = 0; k < PValues.Count; k++)
{
parameters.C = CValues[i];
parameters.Gamma = GammaValues[j];
parameters.P = PValues[k];
double num = Math.Abs(Training.PerformCrossValidation(problem, parameters, nrfold));
Console.Write("{0} {1} {2} {3}", parameters.C, parameters.Gamma, parameters.P, num);
if (!string.IsNullOrEmpty(outputFile))
{
File.AppendAllText(outputFile, string.Format("{0} {1} {2} {3}\n", parameters.C, parameters.Gamma, parameters.P, num));
}
list.Add(new RegressionParameter(parameters.C, parameters.Gamma, parameters.P, num));
}
}
}
list.Sort();
if (MaxBestCount > 0)
{
int l;
for (l = Math.Min(MaxBestCount, list.Count); l < list.Count && l < MaxBestCount * 3 && list[l - 1].SortValue == list[l].SortValue; l++)
{
}
if (list.Count > l)
{
list.RemoveRange(l, list.Count - l);
}
list.TrimExcess();
}
return(list.ToArray());
}
public static void GridRegression(Problem problem, Parameter parameters, List <double> CValues, List <double> GammaValues, List <double> PValues, string outputFile, int nrfold, out double C, out double Gamma, out double P)
{
C = 0.0;
Gamma = 0.0;
P = 0.0;
double num = 1.7976931348623157E+308;
if (!string.IsNullOrEmpty(outputFile))
{
File.WriteAllText(outputFile, string.Empty);
}
for (int i = 0; i < CValues.Count; i++)
{
for (int j = 0; j < GammaValues.Count; j++)
{
for (int k = 0; k < PValues.Count; k++)
{
parameters.C = CValues[i];
parameters.Gamma = GammaValues[j];
parameters.P = PValues[k];
double num2 = Math.Abs(Training.PerformCrossValidation(problem, parameters, nrfold));
Console.Write("{0} {1} {2} {3}", parameters.C, parameters.Gamma, parameters.P, num2);
if (!string.IsNullOrEmpty(outputFile))
{
File.AppendAllText(outputFile, string.Format("{0} {1} {2} {3}\n", parameters.C, parameters.Gamma, parameters.P, num2));
}
if (num2 < num)
{
C = parameters.C;
Gamma = parameters.Gamma;
P = parameters.P;
num = num2;
Console.WriteLine(" New Min!");
}
else
{
Console.WriteLine();
}
}
}
}
}
public static void Grid(Problem problem, Parameter parameters, List <double> CValues, List <double> GammaValues, string outputFile, int nrfold, out double C, out double Gamma)
{
C = 0.0;
Gamma = 0.0;
double num = -1.7976931348623157E+308;
if (!string.IsNullOrEmpty(outputFile))
{
File.WriteAllText(outputFile, string.Empty);
}
for (int i = 0; i < CValues.Count; i++)
{
for (int j = 0; j < GammaValues.Count; j++)
{
parameters.C = CValues[i];
parameters.Gamma = GammaValues[j];
double num2 = Training.PerformCrossValidation(problem, parameters, nrfold);
Console.Write("{0} {1} {2}", parameters.C, parameters.Gamma, num2);
if (!string.IsNullOrEmpty(outputFile))
{
File.AppendAllText(outputFile, string.Format("{0} {1} {2}\n", parameters.C, parameters.Gamma, num2));
}
if (num2 > num)
{
C = parameters.C;
Gamma = parameters.Gamma;
num = num2;
Console.WriteLine(" New Maximum!");
}
else
{
Console.WriteLine();
}
}
}
}
private static double GridCompute(GridComputingParameter Para)
{
return(Training.PerformCrossValidation(Para.problem, Para.parameter, Para.nrfold));
}
public static int SmartGridRegression(Problem problem, Parameter parameter, double C_Start, double C_Multi, double Gamma_Start, double Gamma_Multi, double P_Start, double P_Multi, string outputFile, int nrfold, out double C, out double Gamma, out double P)
{
C = C_Start;
Gamma = Gamma_Start;
P = P_Start;
double num = -1.7976931348623157E+308;
if (!string.IsNullOrEmpty(outputFile))
{
File.WriteAllText(outputFile, string.Empty);
}
int num2 = 0;
double[] array = new double[21]
{
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
C_Start,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0
};
double[] array2 = new double[21]
{
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
Gamma_Start,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0
};
double[] array3 = new double[21]
{
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
P_Start,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0
};
for (int i = 0; i < 10; i++)
{
array[9 - i] = array[10 - i] / C_Multi;
array[11 + i] = array[10 + i] * C_Multi;
array2[9 - i] = array2[10 - i] / Gamma_Multi;
array2[11 + i] = array2[10 + i] * Gamma_Multi;
array3[9 - i] = array3[10 - i] / P_Multi;
array3[11 + i] = array3[10 + i] / P_Multi;
}
double[,,] array4 = new double[21, 21, 21];
Point3D point3D = new Point3D(10, 10, 10);
Point3D[] array5 = ParameterSelection.FindNeedCompute(array4, point3D);
while (array5.Length > 0)
{
for (int j = 0; j < array5.Length; j++)
{
parameter.C = array[array5[j].C];
parameter.Gamma = array2[array5[j].G];
parameter.P = array3[array5[j].P];
double num3 = Training.PerformCrossValidation(problem, parameter, nrfold);
array4[array5[j].C, array5[j].G, array5[j].P] = num3;
Console.Write(string.Format("{0} {1} {2} {3}", array[array5[j].C], array2[array5[j].G], array3[array5[j].P], num3));
if (!string.IsNullOrEmpty(outputFile))
{
File.AppendAllText(outputFile, string.Format("{0} {1} {2} {3}\n", array[array5[j].C], array2[array5[j].G], array3[array5[j].P], num3));
}
if (num3 < num)
{
num = num3;
point3D.C = array5[j].C;
point3D.G = array5[j].G;
point3D.P = array5[j].P;
C = array[array5[j].C];
Gamma = array2[array5[j].G];
P = array3[array5[j].P];
Console.WriteLine(" New Min!");
}
else
{
Console.WriteLine();
}
num2++;
}
array5 = ParameterSelection.FindNeedCompute(array4, point3D);
}
return(num2);
}
public static int SmartGrid(Problem problem, Parameter parameters, double C_Start, double C_Multi, double Gamma_Start, double Gamma_Multi, string outputFile, int nrfold, out double C, out double Gamma, bool Parallel = true)
{
C = C_Start;
Gamma = Gamma_Start;
double num = -1.7976931348623157E+308;
if (!string.IsNullOrEmpty(outputFile))
{
File.WriteAllText(outputFile, string.Empty);
}
int num2 = 0;
double[,] array = new double[21, 21];
double[] array2 = new double[21]
{
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
C_Start,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0
};
double[] array3 = new double[21]
{
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
Gamma_Start,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0,
0.0
};
for (int i = 0; i < 10; i++)
{
array2[9 - i] = array2[10 - i] / C_Multi;
array2[11 + i] = array2[10 + i] * C_Multi;
array3[9 - i] = array3[10 - i] / Gamma_Multi;
array3[11 + i] = array3[10 + i] * Gamma_Multi;
}
Point p = new Point(10, 10);
Point[] array4 = ParameterSelection.FindNeedCompute(array, p, TrendLineDirection.LeftBelow_to_RightHigh);
while (array4.Length > 0)
{
Task <double>[] array5 = new Task <double> [array4.Length];
if (Parallel)
{
for (int j = 0; j < array4.Length; j++)
{
Parameter parameter = (Parameter)parameters.Clone();
parameter.C = array2[array4[j].X];
parameter.Gamma = array3[array4[j].Y];
GridComputingParameter state = new GridComputingParameter(problem, parameter, nrfold);
array5[j] = new Task <double>((object obj) => ParameterSelection.GridCompute((GridComputingParameter)obj), state);
array5[j].Start();
}
}
for (int k = 0; k < array4.Length; k++)
{
double num3;
if (Parallel)
{
num3 = array5[k].Result;
}
else
{
parameters.C = array2[array4[k].X];
parameters.Gamma = array3[array4[k].Y];
num3 = Training.PerformCrossValidation(problem, parameters, nrfold);
}
array[array4[k].X, array4[k].Y] = num3;
Console.Write(string.Format("{0} {1} {2}", array2[array4[k].X], array3[array4[k].Y], num3));
if (!string.IsNullOrEmpty(outputFile))
{
File.AppendAllText(outputFile, string.Format("{0} {1} {2}\n", array2[array4[k].X], array3[array4[k].Y], num3));
}
if (num3 > num)
{
num = num3;
p.X = array4[k].X;
p.Y = array4[k].Y;
C = array2[array4[k].X];
Gamma = array3[array4[k].Y];
Console.WriteLine(" New Maximum!");
}
else
{
Console.WriteLine();
}
num2++;
}
array4 = ParameterSelection.FindNeedCompute(array, p, TrendLineDirection.LeftBelow_to_RightHigh);
}
return(num2);
}
