public void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "PCA Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Sample size = " + n.ToString());
rd.addMessage("Vars: " + String.Join(", ", VariableFieldNames));
rd.addMessage("\nProportions: " + String.Join(", ", (from double d in ProportionOfTotalVariance select d.ToString()).ToArray()));
rd.addMessage("\nEigenValues: " + String.Join(", ", (from double d in EigenValues select d.ToString()).ToArray()));
rd.addMessage("\n\nEigenvectors:\n");
double[,] scov = EigenVectors;
for (int i = 0; i < VariableFieldNames.Length; i++)
{
string[] vlArr = new string[VariableFieldNames.Length];
for (int j = 0; j < VariableFieldNames.Length; j++)
{
vlArr[j] = scov[j, i].ToString();
}
rd.addMessage(String.Join(", ", vlArr));
}
rd.enableClose();
rd.Show();
}
public void getReport(double alpha)
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Regression Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Intercept Through Origin = " + InterceptThroughOrigin.ToString());
rd.addMessage("F-statistic = " + FValue.ToString() + " p-value = " + PValue.ToString());
rd.addMessage("RMSE = " + RMSE.ToString());
rd.addMessage("R2 = " + Rsquared.ToString());
rd.addMessage("Adj-R2 = " + AdjustedRsquared.ToString() + "\n\nCoefficents and standard errors:\n");
rd.addMessage("Param: Intercept, " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Coef: " + string.Join(", ", (from double d in Coefficients select d.ToString()).ToArray()));
rd.addMessage("STE: " + string.Join(", ", (from double d in StandardErrors select d.ToString()).ToArray()) + "\n");
try
{
if (ModelHelper.chartingAvailable())
{
regChart();
}
}
catch
{
System.Windows.Forms.MessageBox.Show("Cannot create charts");
}
rd.Show();
rd.enableClose();
}
public void getReport(double alpha)
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "GLM Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Iteration = " + Iterations.ToString());
rd.addMessage("Delta Convergence " + DeltaC.ToString());
rd.addMessage("Chi-Sqr = " + ChiSquare.ToString() + " p-value = " + PValue.ToString());
rd.addMessage("Deviance = " + Deviance.ToString());
rd.addMessage("Log Likelihood = " + LogLikelihood.ToString());
rd.addMessage("Log Likelihood Ratio = " + LogLikelihoodratio.ToString() + "\n\nCoefficents and standard errors:\n");
rd.addMessage("Param: Intercept, " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Coef: " + string.Join(", ", (from double d in Coefficients select d.ToString()).ToArray()));
rd.addMessage("STE: " + string.Join(", ", (from double d in StdError select d.ToString()).ToArray()) + "\n");
try
{
if (ModelHelper.chartingAvailable() && System.Windows.Forms.MessageBox.Show("Do you want to build distribution 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 void getReport(double alpha)
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Logistic Regression Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("LogLikelihood = " + LogLikelihood.ToString());
rd.addMessage("Deviance = " + Deviance.ToString());
rd.addMessage("Likelihood Ratio Chi-squared = " + X2.ToString() + " DF = " + DegreesOfFredom.ToString() + " p-value = " + PValue.ToString());
rd.addMessage("\n\nClasses: " + String.Join(", ", Categories));
rd.addMessage("Reference Class = " + Categories[0]);
rd.addMessage("\nParameter coefficients:\n");
rd.addMessage("intercept, " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Coef: " + String.Join(" ", (from double d in Coefficients select d.ToString()).ToArray()));
rd.addMessage("STE: " + String.Join(", ", (from double d in StandardError select d.ToString()).ToArray()));
rd.addMessage("\n\nWald stats for coefficients:\nchi-sq: " + String.Join(", ", (from Accord.Statistics.Testing.WaldTest d in WaldStatistic select d.Statistic.ToString()).ToArray()));
rd.addMessage("p-value: " + String.Join(", ", (from Accord.Statistics.Testing.WaldTest d in WaldStatistic select d.PValue.ToString()).ToArray()));
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 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 zonalHelper()
{
rsUtil = new rasterUtil();
tempWksStr = rsUtil.TempConvDir;
rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.TopMost = true;
rd.Show();
}
public static void getReport(string modelPath,double proportion=0.1,double alpha=0.05)
{
esriUtil.Forms.RunningProcess.frmRunningProcessDialog rp = new Forms.RunningProcess.frmRunningProcessDialog(false);
rp.addMessage("Sample size for " + modelPath + " based on variation");
rp.stepPGBar(50);
rp.Show();
dataPrepBase.modelTypes mType = ModelHelper.getModelType(modelPath);
rp.addMessage("Model Type = " + mType.ToString());
try
{
switch (mType)
{
case dataPrepBase.modelTypes.Accuracy:
fillAaReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.LinearRegression:
fillLrReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.MvlRegression:
fillMvrReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.LogisticRegression:
fillLogisticReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.PLR:
fillPlrReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.CovCorr:
fillCovCorr(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.PCA:
fillPcaReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.Cluster:
fillCluserReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.StrataCovCorr:
fillStrataReport(modelPath, rp, proportion, alpha);
break;
default:
rp.addMessage("Can't estimate sample size for this type of model!");
break;
}
}
catch (Exception e)
{
rp.addMessage(e.ToString());
}
finally
{
rp.stepPGBar(100);
rp.enableClose();
}
}
public void getReport(double alpha)
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "PLR Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Iterations = " + NumberOfIterationsToConverge.ToString());
rd.addMessage("Convergence = " + Delta.ToString());
rd.addMessage("LogLikelihood = " + LogLikelihood.ToString());
rd.addMessage("Deviance = " + Deviance.ToString());
rd.addMessage("Likelihood Ratio Chi-squared = " + X2.ToString() + " DF = " + DegreesOfFredom.ToString() + " p-value = " + PValue.ToString());
rd.addMessage("\n\nClasses: " + String.Join(", ", Categories));
rd.addMessage("Reference Class = " + Categories[0]);
rd.addMessage("\nParameter coefficients:\n");
rd.addMessage("intercept, " + String.Join(", ", IndependentFieldNames));
for (int i = 0; i < Coefficients.Length; i++)
{
double[] c = Coefficients[i];
rd.addMessage(String.Join(" ", (from double d in c select d.ToString()).ToArray()));
}
rd.addMessage("\nParameter standard error:");
for (int i = 0; i < StandardError.Length; i++)
{
double[] c = StandardError[i];
rd.addMessage(String.Join(", ", (from double d in c select d.ToString()).ToArray()));
}
rd.addMessage("\nParameter Wald Chi-Squared:");
for (int i = 0; i < WaldStatistic.Length; i++)
{
double[] c = WaldStatistic[i];
rd.addMessage(String.Join(", ", (from double d in c select d.ToString()).ToArray()));
}
rd.addMessage("\nParameter Wald P-value:");
for (int i = 0; i < WaldPvalue.Length; i++)
{
double[] c = WaldPvalue[i];
rd.addMessage(String.Join(", ", (from double d in c select d.ToString()).ToArray()));
}
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)
{
regChart();
//if (mlr == null) mlr = buildModel();
}
}
catch
{
System.Windows.Forms.MessageBox.Show("Cannot create charts");
}
rd.Show();
rd.enableClose();
}
public void getReport()
{
if (mctable == null)
{
buildModel();
}
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Compare Classifications";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Match Paired Comparisons");
string l00 = mctable[0, 0].ToString();
string l01 = mctable[0, 1].ToString();
string l10 = mctable[1, 0].ToString();
string l11 = mctable[1, 1].ToString();
rd.addMessage("-".PadRight(100, '-') + "\n");
string mhd = " Correct Wrong";
rd.addMessage(mhd);
rd.addMessage("-".PadRight(28, '-'));
rd.addMessage("Correct | " + adjustString(l00, 7) + " | " + adjustString(l10, 7) + " |");
rd.addMessage("-".PadRight(28, '-'));
rd.addMessage("Wrong | " + adjustString(l01, 7) + " | " + adjustString(l11, 7) + " |");
rd.addMessage("-".PadRight(28, '-'));
rd.addMessage("McNemar's test for correct values = " + mct.Statistic.ToString() + " DF = " + mct.DegreesOfFreedom.ToString() + " p-value = " + mct.PValue.ToString());
rd.addMessage("-".PadRight(100, '-') + "\n");
rd.addMessage("Kappa comparison of two samples = " + akt.Statistic.ToString() + " DF = 1 p-value = " + akt.PValue.ToString());
rd.addMessage("-".PadRight(100, '-') + "\n");
string[] hdArr = (from s in labels select adjustString(s, 5)).ToArray();
string hd = " | " + String.Join(" | ", hdArr);
rd.addMessage(hd);
rd.addMessage("-".PadRight(hd.Length, '-'));
for (int i = 0; i < hdArr.Length; i++)
{
string lnStr = hdArr[i] + " | ";
for (int j = 0; j < hdArr.Length; j++)
{
lnStr = lnStr + adjustString(g3table[j, i].ToString(), 5) + " | ";
}
rd.addMessage(lnStr);
rd.addMessage("-".PadRight(hd.Length, '-'));
}
rd.addMessage("Bhapkar's test of homogeneity = " + bht.Statistic.ToString() + " DF = " + bht.DegreesOfFreedom.ToString() + " p-value = " + bht.PValue.ToString());
rd.addMessage("Bowker's test of symmetry = " + bkt.Statistic.ToString() + " DF = " + bkt.DegreesOfFreedom.ToString() + " p-value = " + bkt.PValue.ToString());
rd.Show();
rd.enableClose();
}
public void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "SVM Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Sum of Squared Error: " + sserror.ToString());
rd.Show();
rd.enableClose();
}
public void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "LDA Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Means: " + string.Join(", ", (from double d in meanValues select d.ToString()).ToArray()));
rd.addMessage("Standard Dev: " + string.Join(", ", (from double d in stdValues select d.ToString()).ToArray()) + "\n");
rd.Show();
rd.enableClose();
}
public void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Kolmogorov Smirnov Two sample distribution Results (p-value for unequal distributions)";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Vars: " + String.Join(", ", Variables));
rd.addMessage("Perform PCA " + Oridinate.ToString());
rd.addMessage("Strata Field = " + StrataField);
rd.addMessage("\n Label | Statistic | WP value | WS p-value");
rd.addMessage("-".PadRight(48, '-'));
for (int i = 0; i < Labels.Length; i++)
{
string ky = Labels[i];
double stat = StatisticValues[i];
string sVl = stat.ToString();
double vl = PValues[i];
string fVl = vl.ToString();
if (vl < 0.0001)
{
fVl = "p < 0.0001";
}
double wVl = WSpvalues[i];
string wspStr = wVl.ToString();
if (wVl < 0.0001)
{
wspStr = "p < 0.0001";
}
string l = ModelHelper.getValue(ky, 8);
string wp = ModelHelper.getValue(fVl, 10);
string s = ModelHelper.getValue(sVl, 10);
string wsp = ModelHelper.getValue(wspStr, 10);
rd.addMessage(l + " | " + s + " | " + wp + " | " + wsp);
}
rd.addMessage("-".PadRight(48, '-'));
if (ModelHelper.chartingAvailable())
{
createKSchart();
}
rd.enableClose();
rd.Show();
}
public void getReport()
{
if (kmeans == null)
{
buildModel();
}
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Stratified Variance Covariance Correlation Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Input path = " + InPath);
rd.addMessage("Sample size = " + n.ToString() + " proportion of total records = " + prop.ToString());
rd.addMessage("Number of Strata = " + k.ToString());
rd.addMessage("Labels = " + String.Join(", ", lbl.ToArray()));
rd.addMessage("Variables: " + String.Join(" ,", VariableFieldNames));
kmeansReport(rd);
rd.enableClose();
rd.Show();
}
public void getReport()
{
if (cov == null)
{
buildModel();
}
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Variance Covariance Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Sample size = " + n.ToString());
rd.addMessage("Vars: " + String.Join(", ", VariableFieldNames));
rd.addMessage("\nSum: " + String.Join(", ", (from double d in SumsVector select d.ToString()).ToArray()));
rd.addMessage("\nMean: " + String.Join(", ", (from double d in MeanVector select d.ToString()).ToArray()));
rd.addMessage("\n\nSample Variance Covariance:\n");
double[,] scov = CovarianceMatrix;
for (int i = 0; i < SumsVector.Length; i++)
{
string[] vlArr = new string[SumsVector.Length];
for (int j = 0; j < SumsVector.Length; j++)
{
vlArr[j] = scov[j, i].ToString();
}
rd.addMessage(String.Join(", ", vlArr));
}
double[,] corr = CorralationMatrix;
rd.addMessage("\n\nCorr:\n");
for (int i = 0; i < SumsVector.Length; i++)
{
string[] vlArr = new string[SumsVector.Length];
for (int j = 0; j < SumsVector.Length; j++)
{
vlArr[j] = corr[j, i].ToString();
}
rd.addMessage(String.Join(", ", vlArr));
}
rd.Show();
rd.enableClose();
}
public void getReport()
{
if (model == null)
{
buildModel();
}
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Cluster Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Input path = " + InPath);
rd.addMessage("Sample size = " + n.ToString() + " proportion of total records = " + prop.ToString());
rd.addMessage("Number of Cluster = " + k.ToString());
rd.addMessage("Labels = " + String.Join(", ", lbl.ToArray()));
rd.addMessage("Variables: " + String.Join(" ,", VariableFieldNames));
rd.addMessage("Cluster Type: " + cType.ToString());
switch (cType)
{
case clusterType.KMEANS:
kmeansReport(rd);
break;
case clusterType.BINARY:
binaryReport(rd);
break;
case clusterType.GAUSSIANMIXTURE:
gaussianReport(rd);
break;
default:
break;
}
rd.enableClose();
rd.Show();
}
public void getReport()
{
if (kmeans == null)
{
buildModel();
}
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Cluster Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Input path = " + InPath);
rd.addMessage("Sample size = " + n.ToString() + " proportion of total records = " + prop.ToString());
rd.addMessage("Number of Cluster = " + k.ToString());
rd.addMessage("Labels = " + String.Join(", ", lbl.ToArray()));
rd.addMessage("Variables: " + String.Join(" ,", VariableFieldNames));
KMeansClusterCollection gCol = kmeans.Clusters;
for (int i = 0; i < gCol.Count; i++)
{
KMeansCluster gClust = gCol[i];
double[] mns = gClust.Mean;
double[,] cov = gClust.Covariance;
rd.addMessage("\n\nCluster " + Labels[i] + ":\nMeans: " + String.Join(", ", (from double d in mns select d.ToString()).ToArray()) + "\nCovariance:");
for (int j = 0; j < VariableFieldNames.Length; j++)
{
string[] covStrArr = new string[VariableFieldNames.Length];
for (int l = 0; l < covStrArr.Length; l++)
{
covStrArr[l] = cov[l, j].ToString();
}
rd.addMessage("\n" + String.Join(",", covStrArr));
}
}
rd.enableClose();
rd.Show();
}
public void getReport(double alpha)
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Logistic Regression Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("LogLikelihood = " + LogLikelihood.ToString());
rd.addMessage("Deviance = " + Deviance.ToString());
rd.addMessage("Likelihood Ratio Chi-squared = " + X2.ToString() + " DF = " + DegreesOfFredom.ToString() + " p-value = " + PValue.ToString());
rd.addMessage("\n\nClasses: " + String.Join(", ", Categories));
rd.addMessage("Reference Class = " + Categories[0]);
rd.addMessage("\nParameter coefficients:\n");
rd.addMessage("intercept, " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Coef: " +String.Join(" ", (from double d in Coefficients select d.ToString()).ToArray()));
rd.addMessage("STE: " + String.Join(", ", (from double d in StandardError select d.ToString()).ToArray()));
rd.addMessage("\n\nWald stats for coefficients:\nchi-sq: "+ String.Join(", ", (from Accord.Statistics.Testing.WaldTest d in WaldStatistic select d.Statistic.ToString()).ToArray()));
rd.addMessage("p-value: " + String.Join(", ", (from Accord.Statistics.Testing.WaldTest d in WaldStatistic select d.PValue.ToString()).ToArray()));
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 void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "PCA Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Sample size = " + n.ToString());
rd.addMessage("Vars: " + String.Join(", ", VariableFieldNames));
rd.addMessage("\nProportions: " + String.Join(", ", (from double d in ProportionOfTotalVariance select d.ToString()).ToArray()));
rd.addMessage("\nEigenValues: " + String.Join(", ", (from double d in EigenValues select d.ToString()).ToArray()));
rd.addMessage("\n\nEigenvectors:\n");
double[,] scov = EigenVectors;
for (int i = 0; i < VariableFieldNames.Length; i++)
{
string[] vlArr = new string[VariableFieldNames.Length];
for (int j = 0; j < VariableFieldNames.Length; j++)
{
vlArr[j] = scov[j, i].ToString();
}
rd.addMessage(String.Join(", ", vlArr));
}
rd.enableClose();
rd.Show();
}
public void getReport(double alpha)
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "GLM Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Iteration = " + Iterations.ToString());
rd.addMessage("Delta Convergence " + DeltaC.ToString());
rd.addMessage("Chi-Sqr = " + ChiSquare.ToString() + " p-value = " + PValue.ToString());
rd.addMessage("Deviance = " + Deviance.ToString());
rd.addMessage("Log Likelihood = " + LogLikelihood.ToString());
rd.addMessage("Log Likelihood Ratio = " + LogLikelihoodratio.ToString() + "\n\nCoefficents and standard errors:\n");
rd.addMessage("Param: Intercept, " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Coef: " + string.Join(", ", (from double d in Coefficients select d.ToString()).ToArray()));
rd.addMessage("STE: " + string.Join(", ", (from double d in StdError select d.ToString()).ToArray()) + "\n");
try
{
if (ModelHelper.chartingAvailable() && System.Windows.Forms.MessageBox.Show("Do you want to build distribution 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 void getReport()
{
if (kmeans == null) buildModel();
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Stratified Variance Covariance Correlation Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Input path = " + InPath);
rd.addMessage("Sample size = " + n.ToString() + " proportion of total records = " + prop.ToString());
rd.addMessage("Number of Strata = " + k.ToString());
rd.addMessage("Labels = " + String.Join(", ", lbl.ToArray()));
rd.addMessage("Variables: " + String.Join(" ,", VariableFieldNames));
kmeansReport(rd);
rd.enableClose();
rd.Show();
}
public void getReport()
{
if(mctable==null)buildModel();
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Compare Classifications";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Match Paired Comparisons");
string l00 = mctable[0, 0].ToString();
string l01 = mctable[0, 1].ToString();
string l10 = mctable[1, 0].ToString();
string l11 = mctable[1, 1].ToString();
rd.addMessage("-".PadRight(100, '-') + "\n");
string mhd = " Correct Wrong";
rd.addMessage(mhd);
rd.addMessage("-".PadRight(28, '-'));
rd.addMessage("Correct | " + adjustString(l00, 7) + " | " + adjustString(l10, 7) + " |");
rd.addMessage("-".PadRight(28, '-'));
rd.addMessage("Wrong | " + adjustString(l01, 7) + " | " + adjustString(l11, 7) + " |");
rd.addMessage("-".PadRight(28, '-'));
rd.addMessage("McNemar's test for correct values = " + mct.Statistic.ToString() + " DF = " + mct.DegreesOfFreedom.ToString() + " p-value = " + mct.PValue.ToString());
rd.addMessage("-".PadRight(100, '-')+"\n");
rd.addMessage("Kappa comparison of two samples = " + akt.Statistic.ToString() + " DF = 1 p-value = " + akt.PValue.ToString());
rd.addMessage("-".PadRight(100, '-') + "\n");
string[] hdArr = (from s in labels select adjustString(s,5)).ToArray();
string hd = " | " + String.Join(" | ",hdArr);
rd.addMessage(hd);
rd.addMessage("-".PadRight(hd.Length,'-'));
for (int i = 0; i < hdArr.Length; i++)
{
string lnStr = hdArr[i] + " | ";
for (int j = 0; j < hdArr.Length; j++)
{
lnStr = lnStr + adjustString(g3table[j,i].ToString(),5) + " | ";
}
rd.addMessage(lnStr);
rd.addMessage("-".PadRight(hd.Length, '-'));
}
rd.addMessage("Bhapkar's test of homogeneity = " + bht.Statistic.ToString() + " DF = " + bht.DegreesOfFreedom.ToString() + " p-value = " + bht.PValue.ToString());
rd.addMessage("Bowker's test of symmetry = " + bkt.Statistic.ToString() + " DF = " + bkt.DegreesOfFreedom.ToString() + " p-value = " + bkt.PValue.ToString());
rd.Show();
rd.enableClose();
}
public void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "SVM Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Sum of Squared Error: " + sserror.ToString());
rd.Show();
rd.enableClose();
}
public void getReport()
{
if (kmeans == null) buildModel();
rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Independent T-Test Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Input path = " + InPath);
rd.addMessage("Total Sample size = " + n.ToString());
rd.addMessage("\nLabel |Compare V1-V2 |N |Dif |T-Stat |P-Value ");
rd.addMessage("-".PadRight(83,'-'));
KMeansClusterCollection gCol = kmeans.Clusters;
for (int i = 0; i < gCol.Count; i++)
{
string l = getValue(Labels[i],8);
KMeansCluster gClust = gCol[i];
double[] mns = gClust.Mean;
double[] var = new double[mns.Length];
double nSample = gClust.Proportion * N;
if (nSample <= 1) continue;
double seAdjust = Math.Sqrt(2*1/nSample);
for (int j = 0; j < mns.Length; j++)
{
var[j] = gClust.Covariance[j, j];
}
int cnt = 1;
for (int j = 0; j < mns.Length-1; j++)
{
for (int k = cnt; k < mns.Length; k++)
{
string fN1 = getValue(VariableFieldNames[j],12);
string fN2 = getValue(VariableFieldNames[k],12);
double mD = mns[j] - mns[k];
double pSD = Math.Sqrt((var[j] + var[k]) / 2);
double se = pSD * seAdjust;
double tStat = mD / se;
Accord.Statistics.Distributions.Univariate.TDistribution tDist = new Accord.Statistics.Distributions.Univariate.TDistribution(2*nSample-2);
double cdf = tDist.DistributionFunction(tStat);
double pValue = 0;
if (tStat>0)
{
pValue = (1 - cdf) * 2;
}
else
{
pValue = (cdf * 2);
}
string pValueS = pValue.ToString();
if (pValue < 0.0001) pValueS = "p < 0.0001";
string ln = l + "|" + fN1 + "-" + fN2 + "| " + getValue(nSample.ToString(), 6) + " | " + getValue(mD.ToString(), 6) + " | " + getValue(tStat.ToString(), 6) + " | " + getValue(pValueS,10);
rd.addMessage(ln);
}
cnt += 1;
}
}
rd.addMessage("-".PadRight(83, '-'));
rd.enableClose();
rd.Show();
}
new public void getReport()
{
if (cateDic.Count < 1)
{
buildModel();
}
rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Paired T-Test Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Input path = " + InPath);
rd.addMessage("Total Sample size = " + n.ToString());
rd.addMessage("\nLabel |Compare V1-V2 |N |Dif |T-Stat |P-Value ");
rd.addMessage("-".PadRight(83, '-'));
for (int i = 0; i < lbl.Count; i++)
{
string labelVl = Labels[i];
string l = getValue(labelVl, 8);
int gN = cateDic[labelVl];
if (gN == 1)
{
continue;
}
double[] s = sumX[i];
double[] s2 = sumX2[i];
double[] mns = (from double d in s select d / gN).ToArray();
//Console.WriteLine("Means = " + mns.Length.ToString());
double[] ses = getSe(s, s2, gN);
//Console.WriteLine("Se = " + ses.Length.ToString());
double nSample = gN;
int cnt = 1;
int sCnt = 0;
for (int j = 0; j < VariableFieldNames.Length - 1; j++)
{
for (int k = cnt; k < VariableFieldNames.Length; k++)
{
string fN1 = getValue(VariableFieldNames[j], 12);
string fN2 = getValue(VariableFieldNames[k], 12);
double mD = mns[sCnt];
double se = ses[sCnt];
double tStat = mD / se;
//Console.WriteLine(tStat.ToString());
Accord.Statistics.Distributions.Univariate.TDistribution tDist = new Accord.Statistics.Distributions.Univariate.TDistribution(nSample - 1);
double cdf = tDist.DistributionFunction(tStat);
double pValue = 0;
if (tStat > 0)
{
pValue = (1 - cdf) * 2;
}
else
{
pValue = (cdf * 2);
}
string pValueS = pValue.ToString();
if (pValue < 0.0001)
{
pValueS = pValueS = "p < 0.0001";
}
string ln = l + "|" + fN1 + "-" + fN2 + "| " + getValue(nSample.ToString(), 6) + " | " + getValue(mD.ToString(), 6) + " | " + getValue(tStat.ToString(), 6) + " | " + getValue(pValueS, 10);
rd.addMessage(ln);
sCnt += 1;
}
cnt += 1;
}
}
rd.addMessage("-".PadRight(83, '-'));
rd.enableClose();
rd.Show();
}
public void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Random Forest Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Sample size = " + n.ToString());
if (!(Categories == null || Categories.Length == 0))
{
rd.addMessage("Number of Classes = " + NumberOfClasses.ToString());
rd.addMessage("Class Names and order = " + String.Join(", ", Categories));
}
rd.addMessage("Number of Parameters = " + NumberOfVariables.ToString());
rd.addMessage("Number of Trees = " + NumberOfTrees.ToString());
rd.addMessage("Data Ratio = " + Ratio.ToString());
rd.addMessage("Number of Split Variables = " + NumberOfSplitVariables.ToString());
rd.addMessage("Regression model = " + Regression.ToString()+"\n\nTraining Errors:\n");
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("Relative Classification Error = " + RelativeClassificationError.ToString()+"\n\nValidation Errors:\n");
rd.addMessage("OOBRMSE = " + OOBRMSE.ToString());
rd.addMessage("OOBAverage Error = " + OOBAverageError.ToString());
rd.addMessage("OOBAverage Relative Error = " + OOBAverageRelativeError.ToString());
rd.addMessage("OOBAverage Cross Entropy Error = " + OOBAverageCrossEntropyError.ToString());
rd.addMessage("OOBRelative Classification Error = " + OOBRelativeClassificationError.ToString());
try
{
if (ModelHelper.chartingAvailable())
{
if (!Regression)
{
if (System.Windows.Forms.MessageBox.Show("Do you want to build probability graphs?", "Graphs", System.Windows.Forms.MessageBoxButtons.YesNo) == System.Windows.Forms.DialogResult.Yes)
{
getRegChart();
if (variableImportanceGraph)
{
getVariableImportanceChart();
}
}
}
else
{
if (System.Windows.Forms.MessageBox.Show("Do you want to build predicted values graphs?", "Graphs", System.Windows.Forms.MessageBoxButtons.YesNo) == System.Windows.Forms.DialogResult.Yes)
{
getProbChart();
if (variableImportanceGraph)
{
getVariableImportanceChart();
}
}
}
}
}
catch
{
System.Windows.Forms.MessageBox.Show("Cannot create charts");
}
finally
{
rd.Show();
rd.enableClose();
}
}
public void getReport(double alpha)
{
if(gConf==null)buildModel();
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Accuracy Assessment";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
string[] hd = new string[labels.Count];
for (int i = 0; i < hd.Length; i++)
{
string s = labels[i];
if(s.Length>4)
{
hd[i] = s.Substring(0, 4);
}
else
{
hd[i] = s.PadRight(3);
}
}
rd.addMessage(" "+String.Join(" ", hd));
rd.addMessage("------".PadRight((labels.Count+1)*7,'-'));
for (int i = 0; i < labels.Count; i++)
{
string[] lnArr = new string[labels.Count+1];
string vl = labels[i];
if (vl.Length > 4)
{
vl = vl.Substring(0, 4);
}
else
{
vl = vl.PadRight(4);
}
lnArr[0] = vl;
for (int j = 0; j < labels.Count; j++)
{
vl = xtable[i,j].ToString();
if (vl.Length < 4)
{
vl = vl.PadRight(4);
}
lnArr[j + 1] = vl;
}
rd.addMessage(String.Join(" | ", lnArr)+"|");
rd.addMessage("------".PadRight((labels.Count+1) * 7, '-'));
}
Accord.Statistics.Testing.ChiSquareTest ct = new Accord.Statistics.Testing.ChiSquareTest(ChiSquare, System.Convert.ToInt32(Math.Pow(labels.Count - 1, 2)));
rd.addMessage("Chi-square = " + ChiSquare + " DF = " + ct.DegreesOfFreedom.ToString() + " p-value = " + ct.PValue.ToString());
rd.addMessage("Overall = " + Overall.ToString());
rd.addMessage("Kappa = " + Kappa.ToString());
rd.addMessage("STE = " + STE.ToString());
ci conf = getConfidenceInterval(alpha);
rd.addMessage("Kappa CI = " + conf.LowerBound.ToString() + " - " + conf.UpperBound.ToString());
rd.addMessage("Cohen Kappa Variance = " + CohenKappaVariance.ToString());
rd.Show();
rd.enableClose();
}
public void getReport(double alpha)
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "PLR Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Iterations = " + NumberOfIterationsToConverge.ToString());
rd.addMessage("Convergence = " + Delta.ToString());
rd.addMessage("LogLikelihood = " + LogLikelihood.ToString());
rd.addMessage("Deviance = " + Deviance.ToString());
rd.addMessage("Likelihood Ratio Chi-squared = " + X2.ToString() + " DF = " + DegreesOfFredom.ToString() + " p-value = " + PValue.ToString());
rd.addMessage("\n\nClasses: " + String.Join(", ", Categories));
rd.addMessage("Reference Class = " + Categories[0]);
rd.addMessage("\nParameter coefficients:\n");
rd.addMessage("intercept, " + String.Join(", ", IndependentFieldNames));
for (int i = 0; i < Coefficients.Length; i++)
{
double[] c = Coefficients[i];
rd.addMessage(String.Join(" ", (from double d in c select d.ToString()).ToArray()));
}
rd.addMessage("\nParameter standard error:");
for (int i = 0; i < StandardError.Length; i++)
{
double[] c = StandardError[i];
rd.addMessage(String.Join(", ", (from double d in c select d.ToString()).ToArray()));
}
rd.addMessage("\nParameter Wald Chi-Squared:");
for (int i = 0; i < WaldStatistic.Length; i++)
{
double[] c = WaldStatistic[i];
rd.addMessage(String.Join(", ", (from double d in c select d.ToString()).ToArray()));
}
rd.addMessage("\nParameter Wald P-value:");
for (int i = 0; i < WaldPvalue.Length; i++)
{
double[] c = WaldPvalue[i];
rd.addMessage(String.Join(", ", (from double d in c select d.ToString()).ToArray()));
}
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)
{
regChart();
//if (mlr == null) mlr = buildModel();
}
}
catch
{
System.Windows.Forms.MessageBox.Show("Cannot create charts");
}
rd.Show();
rd.enableClose();
}
public static void getReport(string modelPath, double proportion = 0.1, double alpha = 0.05)
{
esriUtil.Forms.RunningProcess.frmRunningProcessDialog rp = new Forms.RunningProcess.frmRunningProcessDialog(false);
rp.addMessage("Sample size for " + modelPath + " based on variation");
rp.stepPGBar(50);
rp.Show();
dataPrepBase.modelTypes mType = ModelHelper.getModelType(modelPath);
rp.addMessage("Model Type = " + mType.ToString());
try
{
switch (mType)
{
case dataPrepBase.modelTypes.Accuracy:
fillAaReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.LinearRegression:
fillLrReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.MvlRegression:
fillMvrReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.LogisticRegression:
fillLogisticReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.PLR:
fillPlrReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.CovCorr:
fillCovCorr(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.PCA:
fillPcaReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.Cluster:
fillCluserReport(modelPath, rp, proportion, alpha);
break;
case dataPrepBase.modelTypes.StrataCovCorr:
fillStrataReport(modelPath, rp, proportion, alpha);
break;
default:
rp.addMessage("Can't estimate sample size for this type of model!");
break;
}
}
catch (Exception e)
{
rp.addMessage(e.ToString());
}
finally
{
rp.stepPGBar(100);
rp.enableClose();
}
}
public void getReport()
{
if (kmeans == null)
{
buildModel();
}
rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Independent T-Test Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Input path = " + InPath);
rd.addMessage("Total Sample size = " + n.ToString());
rd.addMessage("\nLabel |Compare V1-V2 |N |Dif |T-Stat |P-Value ");
rd.addMessage("-".PadRight(83, '-'));
KMeansClusterCollection gCol = kmeans.Clusters;
for (int i = 0; i < gCol.Count; i++)
{
string l = getValue(Labels[i], 8);
KMeansCluster gClust = gCol[i];
double[] mns = gClust.Mean;
double[] var = new double[mns.Length];
double nSample = gClust.Proportion * N;
if (nSample <= 1)
{
continue;
}
double seAdjust = Math.Sqrt(2 * 1 / nSample);
for (int j = 0; j < mns.Length; j++)
{
var[j] = gClust.Covariance[j, j];
}
int cnt = 1;
for (int j = 0; j < mns.Length - 1; j++)
{
for (int k = cnt; k < mns.Length; k++)
{
string fN1 = getValue(VariableFieldNames[j], 12);
string fN2 = getValue(VariableFieldNames[k], 12);
double mD = mns[j] - mns[k];
double pSD = Math.Sqrt((var[j] + var[k]) / 2);
double se = pSD * seAdjust;
double tStat = mD / se;
Accord.Statistics.Distributions.Univariate.TDistribution tDist = new Accord.Statistics.Distributions.Univariate.TDistribution(2 * nSample - 2);
double cdf = tDist.DistributionFunction(tStat);
double pValue = 0;
if (tStat > 0)
{
pValue = (1 - cdf) * 2;
}
else
{
pValue = (cdf * 2);
}
string pValueS = pValue.ToString();
if (pValue < 0.0001)
{
pValueS = "p < 0.0001";
}
string ln = l + "|" + fN1 + "-" + fN2 + "| " + getValue(nSample.ToString(), 6) + " | " + getValue(mD.ToString(), 6) + " | " + getValue(tStat.ToString(), 6) + " | " + getValue(pValueS, 10);
rd.addMessage(ln);
}
cnt += 1;
}
}
rd.addMessage("-".PadRight(83, '-'));
rd.enableClose();
rd.Show();
}
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 void getReport(double alpha)
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Regression Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Intercept Through Origin = " + InterceptThroughOrigin.ToString());
rd.addMessage("F-statistic = " + FValue.ToString() + " p-value = " + PValue.ToString());
rd.addMessage("RMSE = " + RMSE.ToString());
rd.addMessage("R2 = " + Rsquared.ToString());
rd.addMessage("Adj-R2 = " + AdjustedRsquared.ToString() + "\n\nCoefficents and standard errors:\n");
rd.addMessage("Param: Intercept, " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Coef: " + string.Join(", ", (from double d in Coefficients select d.ToString()).ToArray()));
rd.addMessage("STE: " + string.Join(", ", (from double d in StandardErrors select d.ToString()).ToArray()) + "\n");
try
{
if (ModelHelper.chartingAvailable())
{
regChart();
}
}
catch
{
System.Windows.Forms.MessageBox.Show("Cannot create charts");
}
rd.Show();
rd.enableClose();
}
public void getReport()
{
if (model == null) buildModel();
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Cluster Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Input path = " + InPath);
rd.addMessage("Sample size = " + n.ToString() + " proportion of total records = " + prop.ToString());
rd.addMessage("Number of Cluster = " + k.ToString());
rd.addMessage("Labels = " + String.Join(", ", lbl.ToArray()));
rd.addMessage("Variables: " + String.Join(" ,", VariableFieldNames));
rd.addMessage("Cluster Type: " + cType.ToString());
switch (cType)
{
case clusterType.KMEANS:
kmeansReport(rd);
break;
case clusterType.BINARY:
binaryReport(rd);
break;
case clusterType.GAUSSIANMIXTURE:
gaussianReport(rd);
break;
default:
break;
}
rd.enableClose();
rd.Show();
}
public void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "KDA Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Means: " + string.Join(", ", (from double d in meanValues select d.ToString()).ToArray()));
rd.addMessage("Standard Dev: " + string.Join(", ", (from double d in stdValues select d.ToString()).ToArray()) + "\n");
rd.Show();
rd.enableClose();
}
public new void getReport()
{
if (cateDic.Count<1) buildModel();
rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Paired T-Test Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Input path = " + InPath);
rd.addMessage("Total Sample size = " + n.ToString());
rd.addMessage("\nLabel |Compare V1-V2 |N |Dif |T-Stat |P-Value ");
rd.addMessage("-".PadRight(83, '-'));
for (int i = 0; i < lbl.Count; i++)
{
string labelVl = Labels[i];
string l = getValue(labelVl, 8);
int gN = cateDic[labelVl];
if (gN == 1) continue;
double[] s = sumX[i];
double[] s2 = sumX2[i];
double[] mns = (from double d in s select d/gN).ToArray();
//Console.WriteLine("Means = " + mns.Length.ToString());
double[] ses = getSe(s, s2, gN);
//Console.WriteLine("Se = " + ses.Length.ToString());
double nSample = gN;
int cnt = 1;
int sCnt = 0;
for (int j = 0; j < VariableFieldNames.Length-1; j++)
{
for (int k = cnt; k < VariableFieldNames.Length; k++)
{
string fN1 = getValue(VariableFieldNames[j], 12);
string fN2 = getValue(VariableFieldNames[k], 12);
double mD = mns[sCnt];
double se = ses[sCnt];
double tStat = mD / se;
//Console.WriteLine(tStat.ToString());
Accord.Statistics.Distributions.Univariate.TDistribution tDist = new Accord.Statistics.Distributions.Univariate.TDistribution(nSample - 1);
double cdf = tDist.DistributionFunction(tStat);
double pValue = 0;
if (tStat > 0)
{
pValue = (1 - cdf) * 2;
}
else
{
pValue = (cdf * 2);
}
string pValueS = pValue.ToString();
if (pValue < 0.0001) pValueS = pValueS = "p < 0.0001";
string ln = l + "|" + fN1 + "-" + fN2 + "| " + getValue(nSample.ToString(), 6) + " | " + getValue(mD.ToString(), 6) + " | " + getValue(tStat.ToString(), 6) + " | " + getValue(pValueS,10);
rd.addMessage(ln);
sCnt += 1;
}
cnt += 1;
}
}
rd.addMessage("-".PadRight(83, '-'));
rd.enableClose();
rd.Show();
}
public void getReport(double alpha)
{
if (gConf == null)
{
buildModel();
}
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Accuracy Assessment";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
string[] hd = new string[labels.Count];
for (int i = 0; i < hd.Length; i++)
{
string s = labels[i];
if (s.Length > 4)
{
hd[i] = s.Substring(0, 4);
}
else
{
hd[i] = s.PadRight(3);
}
}
rd.addMessage(" " + String.Join(" ", hd));
rd.addMessage("------".PadRight((labels.Count + 1) * 7, '-'));
for (int i = 0; i < labels.Count; i++)
{
string[] lnArr = new string[labels.Count + 1];
string vl = labels[i];
if (vl.Length > 4)
{
vl = vl.Substring(0, 4);
}
else
{
vl = vl.PadRight(4);
}
lnArr[0] = vl;
for (int j = 0; j < labels.Count; j++)
{
vl = xtable[i, j].ToString();
if (vl.Length < 4)
{
vl = vl.PadRight(4);
}
lnArr[j + 1] = vl;
}
rd.addMessage(String.Join(" | ", lnArr) + "|");
rd.addMessage("------".PadRight((labels.Count + 1) * 7, '-'));
}
Accord.Statistics.Testing.ChiSquareTest ct = new Accord.Statistics.Testing.ChiSquareTest(ChiSquare, System.Convert.ToInt32(Math.Pow(labels.Count - 1, 2)));
rd.addMessage("Chi-square = " + ChiSquare + " DF = " + ct.DegreesOfFreedom.ToString() + " p-value = " + ct.PValue.ToString());
rd.addMessage("Overall = " + Overall.ToString());
rd.addMessage("Kappa = " + Kappa.ToString());
rd.addMessage("STE = " + STE.ToString());
ci conf = getConfidenceInterval(alpha);
rd.addMessage("Kappa CI = " + conf.LowerBound.ToString() + " - " + conf.UpperBound.ToString());
rd.addMessage("Cohen Kappa Variance = " + CohenKappaVariance.ToString());
rd.Show();
rd.enableClose();
}
public void getReport()
{
if (cov == null) buildModel();
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Variance Covariance Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Sample size = " + n.ToString());
rd.addMessage("Vars: " + String.Join(", ", VariableFieldNames));
rd.addMessage("\nSum: " + String.Join(", ", (from double d in SumsVector select d.ToString()).ToArray()));
rd.addMessage("\nMean: " + String.Join(", ", (from double d in MeanVector select d.ToString()).ToArray()));
rd.addMessage("\n\nSample Variance Covariance:\n");
double[,] scov = CovarianceMatrix;
for (int i = 0; i < SumsVector.Length; i++)
{
string[] vlArr = new string[SumsVector.Length];
for (int j = 0; j < SumsVector.Length; j++)
{
vlArr[j] = scov[j, i].ToString();
}
rd.addMessage(String.Join(", ", vlArr));
}
double[,] corr = CorralationMatrix;
rd.addMessage("\n\nCorr:\n");
for (int i = 0; i < SumsVector.Length; i++)
{
string[] vlArr = new string[SumsVector.Length];
for (int j = 0; j < SumsVector.Length; j++)
{
vlArr[j] = corr[j, i].ToString();
}
rd.addMessage(String.Join(", ", vlArr));
}
rd.Show();
rd.enableClose();
}
public void getReport()
{
if (kmeans == null) buildModel();
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Cluster Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Input path = " + InPath);
rd.addMessage("Sample size = " + n.ToString() + " proportion of total records = " + prop.ToString() );
rd.addMessage("Number of Cluster = " + k.ToString());
rd.addMessage("Labels = " + String.Join(", ", lbl.ToArray()));
rd.addMessage("Variables: " + String.Join(" ,", VariableFieldNames));
KMeansClusterCollection gCol = kmeans.Clusters;
for (int i = 0; i < gCol.Count; i++)
{
KMeansCluster gClust = gCol[i];
double[] mns = gClust.Mean;
double[,] cov = gClust.Covariance;
rd.addMessage("\n\nCluster " + Labels[i] + ":\nMeans: " + String.Join(", ", (from double d in mns select d.ToString()).ToArray()) + "\nCovariance:");
for (int j = 0; j < VariableFieldNames.Length; j++)
{
string[] covStrArr = new string[VariableFieldNames.Length];
for (int l = 0; l < covStrArr.Length; l++)
{
covStrArr[l] = cov[l, j].ToString();
}
rd.addMessage("\n" + String.Join(",", covStrArr));
}
}
rd.enableClose();
rd.Show();
}
public void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Kolmogorov Smirnov Two sample distribution Results (p-value for unequal distributions)";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Vars: " + String.Join(", ", Variables));
rd.addMessage("Perform PCA " + Oridinate.ToString());
rd.addMessage("Strata Field = " + StrataField);
rd.addMessage("\n Label | Statistic | WP value | WS p-value");
rd.addMessage("-".PadRight(48,'-'));
for (int i = 0; i < Labels.Length; i++)
{
string ky = Labels[i];
double stat = StatisticValues[i];
string sVl = stat.ToString();
double vl = PValues[i];
string fVl = vl.ToString();
if (vl < 0.0001) fVl = "p < 0.0001";
double wVl = WSpvalues[i];
string wspStr = wVl.ToString();
if (wVl < 0.0001) wspStr = "p < 0.0001";
string l = ModelHelper.getValue(ky,8);
string wp = ModelHelper.getValue(fVl,10);
string s = ModelHelper.getValue(sVl, 10);
string wsp = ModelHelper.getValue(wspStr, 10);
rd.addMessage(l + " | " + s +" | " + wp + " | " + wsp);
}
rd.addMessage("-".PadRight(48, '-'));
if (ModelHelper.chartingAvailable())
{
createKSchart();
}
rd.enableClose();
rd.Show();
}