public override Parameters[][] FromSample(ClassifiedSample <double[]> sample)
{
var dim = sample.GetDimension();
var classes = sample.CachedClasses;
var ts = new double[classes.Count];
var result = new Parameters[classes.Count][];
var temp = new double[classes.Count][];
foreach (var cls in classes)
{
result[cls.Value] = new Parameters[dim];
temp[cls.Value] = new double[dim];
}
for (int i = 0; i < dim; i++)
{
foreach (var pData in sample)
{
var data = pData.Key;
var cls = pData.Value;
var p = data[i];
temp[cls.Value][i] += p;
ts[cls.Value] += p;
}
}
foreach (var cls in classes)
{
var tmps = temp[cls.Value];
var rs = result[cls.Value];
var bs = ts[cls.Value];
if (UseSmoothing)
{
bs += m_Alpha * m_N;
}
for (int i = 0; i < dim; i++)
{
var p = tmps[i];
if (UseSmoothing)
{
p += m_Alpha;
}
rs[i] = new Parameters(p / bs);
}
}
return(result);
}
public override Parameters[][] FromSample(ClassifiedSample <double[]> sample)
{
var dim = sample.GetDimension();
var classes = sample.CachedClasses;
var mus = new double[classes.Count];
var mys = new double[classes.Count];
var result = new Parameters[classes.Count][];
foreach (var cls in classes)
{
result[cls.Value] = new Parameters[dim];
}
foreach (var cls in classes)
{
mus[cls.Value] = 0.0D;
mys[cls.Value] = 0;
}
for (int i = 0; i < dim; i++)
{
foreach (var pData in sample)
{
var data = pData.Key;
var cls = pData.Value;
mus[cls.Value] += data[i];
if (i == 0)
{
mys[cls.Value]++;
}
}
foreach (var cls in classes)
{
var mu = mus[cls.Value] / mys[cls.Value];
result[cls.Value][i] = new Parameters(mu);
mus[cls.Value] = 0.0D;
}
}
return(result);
}
public override Parameters[][] FromSample(ClassifiedSample <double[]> sample)
{
var dim = sample.GetDimension();
var classes = sample.CachedClasses;
var mus = new double[classes.Count];
var sigmas = new double[classes.Count];
var mys = new double[classes.Count];
var result = new Parameters[classes.Count][];
foreach (var cls in classes)
{
result[cls.Value] = new Parameters[dim];
}
foreach (var cls in classes)
{
mus[cls.Value] = 0.0D;
sigmas[cls.Value] = 0.0D;
mys[cls.Value] = 0;
}
for (int i = 0; i < dim; i++)
{
foreach (var pData in sample)
{
var data = pData.Key;
var cls = pData.Value;
mus[cls.Value] += data[i];
if (i == 0)
{
mys[cls.Value]++;
}
}
foreach (var cls in classes)
{
mus[cls.Value] /= mys[cls.Value];
}
foreach (var pData in sample)
{
var data = pData.Key;
var cls = pData.Value;
var t = data[i] - mus[cls.Value];
sigmas[cls.Value] += t * t;
}
foreach (var cls in classes)
{
var sigma = Math.Sqrt(sigmas[cls.Value] / mys[cls.Value]);
if (UseSigmaMinThreshold && sigma < SigmaMinThreshold)
{
sigma = SigmaMinThreshold;
}
result[cls.Value][i] = new Parameters(mus[cls.Value], sigma);
mus[cls.Value] = 0.0D;
sigmas[cls.Value] = 0.0D;
}
}
return(result);
}