public string writeModel(string outModelPath)
{
outPath = outModelPath;
using (System.IO.StreamWriter sw = new System.IO.StreamWriter(outPath))
{
sw.WriteLine(modelTypes.LinearRegression.ToString());
sw.WriteLine(InTablePath);
sw.WriteLine(String.Join(",", IndependentFieldNames));
sw.WriteLine(String.Join(",", DependentFieldNames));
sw.WriteLine(String.Join(",", ClassFieldNames));
sw.WriteLine(SampleSize.ToString());
sw.WriteLine(NumberOfVariables.ToString());
sw.WriteLine(InterceptThroughOrigin.ToString());
sw.WriteLine(RMSE);
sw.WriteLine(FValue.ToString());
sw.WriteLine(PValue.ToString());
sw.WriteLine(Rsquared.ToString());
sw.WriteLine(AdjustedRsquared.ToString());
sw.WriteLine(String.Join(" ", (from double d in Coefficients select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in StandardErrors select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in minValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in maxValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in sumValues select d.ToString()).ToArray()));
sw.Close();
}
return(outPath);
}
public string writeModel(string outModelPath)
{
outPath = outModelPath;
string outPathSvm = outModelPath.Replace(".mdl", ".svm");
svmMachine.Save(outPathSvm);
using (System.IO.StreamWriter sw = new System.IO.StreamWriter(outPath))
{
sw.WriteLine(modelTypes.SVM.ToString());
sw.WriteLine(InTablePath);
sw.WriteLine(String.Join(",", IndependentFieldNames));
sw.WriteLine(String.Join(",", DependentFieldNames));
if (ClassFieldNames != null)
{
sw.WriteLine(String.Join(",", ClassFieldNames));
}
else
{
sw.WriteLine();
}
sw.WriteLine(SampleSize.ToString());
sw.WriteLine(NumberOfVariables.ToString());
sw.WriteLine(sserror.ToString());
sw.WriteLine(kTyp.ToString());
sw.WriteLine(String.Join(" ", (from double d in minValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in maxValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in sumValues select d.ToString()).ToArray()));
sw.Close();
}
return(outPath);
}
public string writeModel(string outModelPath)
{
outPath = outModelPath;
using (System.IO.StreamWriter sw = new System.IO.StreamWriter(outPath))
{
sw.WriteLine(modelTypes.GLM.ToString());
sw.WriteLine(InTablePath);
sw.WriteLine(String.Join(",", IndependentFieldNames));
sw.WriteLine(String.Join(",", DependentFieldNames));
sw.WriteLine(String.Join(",", ClassFieldNames));
sw.WriteLine(SampleSize.ToString());
sw.WriteLine(NumberOfVariables.ToString());
sw.WriteLine(Iterations.ToString());
sw.WriteLine(DeltaC.ToString());
sw.WriteLine(LogLikelihood);
sw.WriteLine(LogLikelihoodratio);
sw.WriteLine(PValue.ToString());
sw.WriteLine(Deviance.ToString());
sw.WriteLine(ChiSquare.ToString());
sw.WriteLine(linkfunction.ToString());
sw.WriteLine(String.Join(" ", (from double d in Coefficients select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in StdError select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in waldTestValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in waldTestPValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in minValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in maxValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in sumValues select d.ToString()).ToArray()));
sw.Close();
}
return(outPath);
}
public string writeModel(string outModelPath)
{
if (lm == null)
{
getMnlModel();
}
outPath = outModelPath;
double[,] coef = null;
alglib.mnlunpack(lm, out coef, out nvars, out nclasses);
using (System.IO.StreamWriter sw = new System.IO.StreamWriter(outPath))
{
sw.WriteLine(modelTypes.SoftMax.ToString());
sw.WriteLine(InTablePath);
sw.WriteLine(SampleSize.ToString());
sw.WriteLine(String.Join(",", IndependentFieldNames));
sw.WriteLine(String.Join(",", DependentFieldNames));
sw.WriteLine(String.Join(",", ClassFieldNames));
sw.WriteLine(string.Join(",", Categories));
sw.WriteLine(NumberOfVariables.ToString());
sw.WriteLine(NumberOfClasses.ToString());
sw.WriteLine(RMSE.ToString());
sw.WriteLine(AverageCrossEntropyError.ToString());
sw.WriteLine(AverageError.ToString());
sw.WriteLine(AverageRelativeError.ToString());
sw.WriteLine(ClassificationError.ToString());
sw.WriteLine(RelativeClassificationError.ToString());
sw.WriteLine(String.Join(",", (from double d in minValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(",", (from double d in maxValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(",", (from double d in sumValues select d.ToString()).ToArray()));
int rws = coef.GetUpperBound(1);
int clms = coef.GetUpperBound(0);
for (int r = 0; r <= rws; r++)
{
string[] ln = new string[clms + 1];
for (int c = 0; c <= clms; c++)
{
ln[c] = coef[c, r].ToString();
}
sw.WriteLine(String.Join(" ", ln));
}
sw.Close();
}
return(outPath);
}
public string writeModel(string outModelPath)
{
outPath = outModelPath;
using (System.IO.StreamWriter sw = new System.IO.StreamWriter(outPath))
{
sw.WriteLine(modelTypes.LDA.ToString());
sw.WriteLine(InTablePath);
sw.WriteLine(String.Join(",", IndependentFieldNames));
sw.WriteLine(String.Join(",", DependentFieldNames));
sw.WriteLine(String.Join(",", ClassFieldNames));
sw.WriteLine(SampleSize.ToString());
sw.WriteLine(NumberOfVariables.ToString());
sw.WriteLine(String.Join(" ", (from double d in minValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in maxValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in sumValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in meanValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in stdValues select d.ToString()).ToArray()));
sw.Close();
}
return(outPath);
}