public void getReport()
{
if (lm == null)
{
getMnlModel();
}
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Soft Max Nnet Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Sample size = " + n.ToString());
rd.addMessage("Number of Classes = " + NumberOfClasses.ToString());
rd.addMessage("Number of Parameters = " + nvars.ToString());
rd.addMessage("RMSE = " + RMSE.ToString());
rd.addMessage("Average Error = " + AverageError.ToString());
rd.addMessage("Average Relative Error = " + AverageRelativeError.ToString());
rd.addMessage("Average Cross Entropy Error = " + AverageCrossEntropyError.ToString());
rd.addMessage("Classification Error = " + ClassificationError.ToString());
rd.addMessage("Relative Classification Error = " + RelativeClassificationError.ToString());
try
{
if (ModelHelper.chartingAvailable() && System.Windows.Forms.MessageBox.Show("Do you want to build probability graphs?", "Graphs", System.Windows.Forms.MessageBoxButtons.YesNo) == System.Windows.Forms.DialogResult.Yes)
{
createRegChart();
}
}
catch
{
System.Windows.Forms.MessageBox.Show("Cannot create charts");
}
rd.Show();
rd.enableClose();
}
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);
}
