/// <summary>
/// Estimated closeness of given point to given classes
/// </summary>
public override double CalculateClassScore(double[] obj, Class cls)
{
var score = 0.0D;
var dim = DataDim;
var useMin = UseKernelMinValue;
var min = KernelMinValue;
foreach (var pData in TrainingSample.Where(d => d.Value.Equals(cls)))
{
var data = pData.Key;
var p = 0.0D;
for (int i = 0; i < dim; i++)
{
var h = (m_Hs != null) ? m_Hs[i] : H;
var r = (obj[i] - data[i]) / h;
var v = Kernel.Value(r) / h;
if (Math.Abs(v) < min && useMin)
{
v = min;
}
p += Math.Log(v);
}
score += p;
}
score += PriorProbs[cls.Value];
return(score);
}
/// <summary>
/// Estimated closeness of given point to given classes
/// </summary>
public override double CalculateClassScore(double[] obj, Class cls)
{
var dim = DataDim;
var p = 0.0D;
var y = 0.0D;
var my = ClassHist[cls.Value];
var useMin = UseKernelMinValue;
var min = KernelMinValue;
for (int i = 0; i < dim; i++)
{
foreach (var pData in TrainingSample.Where(d => d.Value.Equals(cls)))
{
var data = pData.Key;
var r = (obj[i] - pData.Key[i]) / H;
p += Kernel.Value(r);
}
p = p / (H * my);
if (Math.Abs(p) < min && useMin)
{
p = min;
}
y += Math.Log(p);
p = 0.0D;
}
y += PriorProbs[cls.Value];
return(y);
}
/// <summary>
/// Estimates closeness of given point to given classes
/// </summary>
public override double CalculateClassScore(double[] obj, Class cls)
{
var score = 0.0D;
foreach (var pData in TrainingSample.Where(d => d.Value.Equals(cls)))
{
var r = Metric.Dist(pData.Key, obj) / H;
score += Kernel.Value(r);
}
score = Math.Log(score) + PriorProbs[cls.Value];
return(score);
}
/// <summary>
/// Estimated proximity of given point to given classes
/// </summary>
public override double CalculateClassScore(double[] obj, Class cls)
{
var dim = TrainingSample.GetDimension();
var p = PriorProbs[cls.Value];
var ds = m_DistributionParameters[cls.Value];
foreach (var pData in TrainingSample.Where(d => d.Value.Equals(cls)))
{
var data = pData.Key;
for (int i = 0; i < dim; i++)
{
m_Distribution.Params = ds[i];
var value = m_Distribution.LogValue(obj[i]);
p += value;
}
}
return(p);
}