public void Constructor_CalculateTruePositivesAndFalseNegative()
{
var inputs = new double[] { 1.0, 2.0, 3.0, 4.0 };
var oftc = new ObjectFromTargetClass(inputs, ComparisonKind.GreaterThanOrEqual, 3.0);
Assert.AreEqual(2, oftc.FalseNegatives);
Assert.AreEqual(2, oftc.TruePositives);
}
public SplitInformation(double[] inputs, double[] validateInputs, int validationInputsTotalCount, ComparisonKind comparisonKind, double splitValue, int learn)
{
var validationPositives = validateInputs.GetVeryfiedCount(comparisonKind, splitValue);
ConfusionMatrix = new ObjectFromTargetClass(inputs, comparisonKind, splitValue);
if (ConfusionMatrix.TruePositives == 0 || validationPositives == 0)
{
RecallValue = 0;
Probability = 0;
MeasureValue = 0;
return;
}
RecallValue
= (double)ConfusionMatrix.TruePositives / learn;
Probability
= (double)validationPositives / validationInputsTotalCount;
MeasureValue
= StatisticsCalculator.CalculateObjectiveFunction(RecallValue, Probability);
}
