private List <Kmeans> RecursiveProcessing(Kmeans parent, List <Kmeans> register)
{
var child1 = new Kmeans(_k, parent.ClusterPoints.Where(x => x.ClusterIndex == 0).Select(x => x.Point).ToList());
var child2 = new Kmeans(_k, parent.ClusterPoints.Where(x => x.ClusterIndex == 1).Select(x => x.Point).ToList());
child1.Calculation(1);
child2.Calculation(1);
if (parent.CenterDistDispersion[0] > child1.CenterDistDispersion[0] + child1.CenterDistDispersion[1]
// if( parent.BICs[0] > child1.BICs[0] + child1.BICs[1]
&& child1.ClusterPoints.Count > 1)
{
RecursiveProcessing(child1, register);
}
else
{
register.Add(child1);
}
if (parent.CenterDistDispersion[1] > child2.CenterDistDispersion[0] + child2.CenterDistDispersion[1]
// if(parent.BICs[1] > child2.BICs[0] + child2.BICs[1]
&& child2.ClusterPoints.Count > 1)
{
RecursiveProcessing(child2, register);
}
else
{
register.Add(child2);
}
return(register);
}
public List <Kmeans> Calculation()
{
TopKm.Calculation(1);
var src = new List <Kmeans>();
var result = RecursiveProcessing(TopKm, src);
return(result);
}
private List<Kmeans> RecursiveProcessing(Kmeans parent, List<Kmeans> register)
{
var child1 = new Kmeans(_k, parent.ClusterPoints.Where(x => x.ClusterIndex == 0).Select(x => x.Point).ToList());
var child2 = new Kmeans(_k, parent.ClusterPoints.Where(x => x.ClusterIndex == 1).Select(x => x.Point).ToList());
child1.Calculation(1);
child2.Calculation(1);
if (parent.CenterDistDispersion[0] > child1.CenterDistDispersion[0] + child1.CenterDistDispersion[1]
// if( parent.BICs[0] > child1.BICs[0] + child1.BICs[1]
&& child1.ClusterPoints.Count > 1)
{
RecursiveProcessing(child1, register);
}
else register.Add(child1);
if (parent.CenterDistDispersion[1] > child2.CenterDistDispersion[0] + child2.CenterDistDispersion[1]
// if(parent.BICs[1] > child2.BICs[0] + child2.BICs[1]
&& child2.ClusterPoints.Count > 1)
{
RecursiveProcessing(child2, register);
}
else register.Add(child2);
return register;
}