public void FindClassificationErrorFullPossibility()
{
double step = 0.00001;
Class1ErrorAssignmentChance = 0;
Class1ErrorNotAssignedChance = 0;
DoubleRange range1 = NormalDistributionClass1.GetRange(0.99);
DoubleRange range2 = NormalDistributionClass2.GetRange(0.99);
double begin = range2.Min;
double end = FindDistributionEqualityPoint();
double f1(double x) => Chance2 / Math.Sqrt(Variance2 * 2 * Math.PI)
* Math.Exp(Math.Pow((x - Mean2), 2) / (-2 * Variance2));
Class1ErrorAssignmentChance = DoubleExponentialTransformation.Integrate(f1, begin, end, 1e-5);
begin = end;
end = range1.Max;
double f2(double x) => Chance1 / Math.Sqrt(Variance1 * 2 * Math.PI)
* Math.Exp(Math.Pow((x - Mean1), 2) / (-2 * Variance1));
Class1ErrorNotAssignedChance = DoubleExponentialTransformation.Integrate(f2, begin, end, 1e-5);
//double x = Math.Min(range1.Min, range2.Min);
//double max = Math.Max(range2.Max, range1.Max);
//bool equalityPointPassed = false;
//while (x < max)
//{
// double dens1 = NormalDistributionClass1.ProbabilityDensityFunction(x);
// double dens2 = NormalDistributionClass2.ProbabilityDensityFunction(x);
// if (!equalityPointPassed)
// Class1ErrorAssignmentChance += dens2 * chance2;
// else
// Class1ErrorNotAssignedChance += dens1 * chance1;
// if (Math.Abs(dens1 - dens2) < 0.00003)
// equalityPointPassed = true;
// x += step;
//}
}
public double FindDistributionEqualityPoint(double step = 0.0001, double accuracy = 0.0001)
{
DoubleRange range1 = NormalDistributionClass1.GetRange(0.99);
DoubleRange range2 = NormalDistributionClass2.GetRange(0.99);
double x = Math.Min(range1.Min, range2.Min);
double max = Math.Max(range2.Max, range1.Max);
while (x < max)
{
double dens1 = NormalDistributionClass1.ProbabilityDensityFunction(x) * Chance1;
double dens2 = NormalDistributionClass2.ProbabilityDensityFunction(x) * Chance2;
if (Math.Abs(dens1 - dens2) < accuracy)
{
return(x);
}
x += step;
}
throw new InvalidOperationException();
}
