/// <summary>
/// populates the roc table (list) with information for the selected model
/// </summary>
/// <param name="data"></param>
private void updateList(List<object> data)
{
listView4.Items.Clear();
foreach (object element in data)
{
ROCParameters rocp = new ROCParameters((object[])element);
string[] item = new string[5];
item[0] = rocp.DecisionThreshold.ToString("f4");
item[3] = rocp.Specificity.ToString("f4");
item[4] = rocp.Sensitivity.ToString("f4");
item[1] = rocp.FalsePosCount.ToString("n0");
item[2] = rocp.FalseNegCount.ToString("n0");
ListViewItem lvi = new ListViewItem(item);
listView4.Items.Add(lvi);
}
}
/// <summary>
/// given a model and decision threshold calculate (and store) information for a roc curve
/// </summary>
/// <param name="model">mlr model</param>
/// <param name="decisionThreshold">threshold value</param>
/// <param name="rocPars">roc curve information </param>
/// <returns>point pair for plotting</returns>
private PointPair ROCpoint(MLRIndividual model, double decisionThreshold, out ROCParameters rocPars)
{
//for a given threshold and model, categorize predictions relative to observations
//and calculate the sensitivity and specificity evaluation criteria, return theses
//values as a zedgraph point.
PointPair pp = new PointPair();
double[] measurement = model.ObservedValues;
double[] est = model.PredictedValues;
int truePos = 0;
int trueNeg = 0;
int falsePos = 0;
int falseNeg = 0;
double pred = double.NaN;
double obs = double.NaN;
double specificity = double.NaN;
double sensitivity = double.NaN;
for (int i = 0; i < est.Length; i++)
{
pred = est[i];
obs = measurement[i];
if ((pred > decisionThreshold) && (obs > _mandateThreshold))
truePos++;
else if ((pred > decisionThreshold) && (obs < _mandateThreshold))
falsePos++;
else if ((pred < decisionThreshold) && (obs > _mandateThreshold))
falseNeg++;
else if ((pred < decisionThreshold) && (obs < _mandateThreshold))
trueNeg++;
}
sensitivity = (double)truePos / (double)(truePos + falseNeg);
specificity = (double)trueNeg / (double)(trueNeg + falsePos);
if (!sensitivity.Equals(double.NaN) && !specificity.Equals(double.NaN))
{
pp.X = (1.0d - specificity);
pp.Y = sensitivity;
}
ROCParameters rocpars = new ROCParameters(decisionThreshold, sensitivity, specificity, falsePos, falseNeg);
rocPars = rocpars;
return pp;
}
