private void buttonROC_Click(object sender, EventArgs e)
{
ReceiverOperatingCharacteristic roc = null;
int numPoints = -1;
string numPointsStr = "";
Utility.InputBox("ROC Points", "How many points should be used?", ref numPointsStr);
if (numPointsStr != "")
{
if (!Int32.TryParse(numPointsStr, out numPoints))
{
MessageBox.Show("Your input was invalid. Please try again.");
return;
}
}
switch (_scheme)
{
case VotingScheme.NONE:
{
roc = _voter.getROC();
break;
}
case VotingScheme.MAJORITY_VOTE:
{
roc = _voter.getMajorityVote().getROC();
break;
}
case VotingScheme.ADDITIVE_PREDICTIONS:
{
roc = _voter.getSumPredictions().getROC();
break;
}
default:
{
break;
}
}
if (roc != null)
{
roc.Compute(numPoints);
FormDataView <double> f = new FormDataView <double>(roc);
f.Show();
}
else
{
if (MessageBox.Show(this, "This voter does not offer ROC computation.\nWould you like to compute a general (non-vote) ROC from the data?", "ROC Computation", MessageBoxButtons.YesNo) == System.Windows.Forms.DialogResult.Yes)
{
roc = _voter.getROC();
roc.Compute(numPoints);
FormDataView <double> f = new FormDataView <double>(roc);
f.Show();
}
}
}
public void testSVM()
{
if (_svm == null)
{
return;
}
int[] output = new int[_outputs.Length];
// Compute the machine outputs
for (int i = 0; i < _outputs.Length; i++)
{
double actual = _outputs[i];
double predicted = _svm.Compute(_inputs[i]);
// System.Console.WriteLine(Math.Sign(actual) + " " + _names[i] + " => " + predicted + " => " + Math.Sign(predicted));
output[i] = System.Math.Sign(predicted);
}
// Use confusion matrix to compute some performance metrics
ConfusionMatrix confusionMatrix = new ConfusionMatrix(output, _outputs, 1, -1);
FormDataView <double> f = new FormDataView <double>(new[] { confusionMatrix });
f.Show();
//dgvPerformance.DataSource = new[] { confusionMatrix };
}
private void buttonShowGeneric_Click(object sender, EventArgs e)
{
FormDataView <double> f = new FormDataView <double>(new[] { _voter.AggregatedConfusionMatrix });
f.Show();
}
internal void showSummary()
{
if (_tableSummary == null)
{
_tableSummary = new DataTable();
_tableSummary.Columns.Add("Category");
_tableSummary.Columns.Add("Samples");
_tableSummary.Columns.Add("AP");
_tableSummary.Columns.Add("AN");
_tableSummary.Columns.Add("TP");
_tableSummary.Columns.Add("FP");
_tableSummary.Columns.Add("TN");
_tableSummary.Columns.Add("FN");
_tableSummary.Columns.Add("Predictions/Node", typeof(String));
_tableSummary.Columns.Add("AP-CM");
_tableSummary.Columns.Add("AN-CM");
_tableSummary.Columns.Add("TP-CM");
_tableSummary.Columns.Add("FP-CM");
_tableSummary.Columns.Add("TN-CM");
_tableSummary.Columns.Add("FN-CM");
_tableSummary.Columns.Add("Sensitivity");
_tableSummary.Columns.Add("FPR");
_tableSummary.Columns.Add("Precision");
_tableSummary.Columns.Add("AUC");
_tableSummary.Columns.Add("FScore");
//_tableSummary.Columns.Add("Num Predictions", typeof(String));
//_tableSummary.Columns.Add("Correct", typeof(String));
//_tableSummary.Columns.Add("False", typeof(String));
//_tableSummary.Columns.Add("Total Votes (Nodes)", typeof(String));
//_tableSummary.Columns.Add("Correct Votes", typeof(String));
//_tableSummary.Columns.Add("False Votes", typeof(String));
//_tableSummary.Columns.Add("Sensitivity (TPR)", typeof(String));
//_tableSummary.Columns.Add("Specificity (TNR)", typeof(String));
//_tableSummary.Columns.Add("Precision (PPV)", typeof(String));
//_tableSummary.Columns.Add("Accuracy", typeof(String));
//_tableSummary.Columns.Add("FPR", typeof(String));
//_tableSummary.Columns.Add("FDR", typeof(String));
_tableSummary.Rows.Add("Base",
Samples, AP, AN, TP, FP, TN, FN,
_numPredictionsPerNode.ToString(),
_baseMatrix.ActualPositives,
_baseMatrix.ActualNegatives,
_baseMatrix.TruePositives,
_baseMatrix.FalsePositives,
_baseMatrix.TrueNegatives,
_baseMatrix.FalseNegatives,
_baseMatrix.Sensitivity,
_baseMatrix.FalsePositiveRate,
_baseMatrix.Precision,
rocAreaBase,
_baseMatrix.FScore);
_tableSummary.Rows.Add("Voter",
VSamples, VAP, VAN, VTP, VFP, VTN, VFN,
_numPredictionsPerNode.ToString(),
_voterMatrix.ActualPositives,
_voterMatrix.ActualNegatives,
_voterMatrix.TruePositives,
_voterMatrix.FalsePositives,
_voterMatrix.TrueNegatives,
_voterMatrix.FalseNegatives,
_voterMatrix.Sensitivity,
_voterMatrix.FalsePositiveRate,
_voterMatrix.Precision,
rocAreaVoter,
_voterMatrix.FScore);
//_tableSummary.Rows.Add(VSamples, VAP, VAN, VTP, VFP, VTN, VFN, _numPredictionsPerNode.ToString(), _voterMatrix.ActualNegatives, _voterMatrix.ActualPositives, _voterMatrix.TruePositives, _voterMatrix.FalsePositives, _voterMatrix.TrueNegatives, _voterMatrix.FalseNegatives);
}
FormDataView <string> f = new FormDataView <string>(_tableSummary);
f.Show();
}
internal void showDetails()
{
FormDataView <string> f = new FormDataView <string>(_tableDetails);
f.Show();
}
