ClusterAnalysis Class

SystemObject
  CenterSpace.NMath.CoreClusterAnalysis

public class ClusterAnalysis : ICloneable

Public Class ClusterAnalysis
	Implements ICloneable

public ref class ClusterAnalysis : ICloneable

type ClusterAnalysis = 
    class
        interface ICloneable
    end

Instances of class ClusterAnalysis are constructed from a matrix of data, where each row in the matrix represents an object to be clustered. Initially, each object is assigned to its own singleton cluster and then the analysis proceeds iteratively, at each stage joining the two most similar clusters into a new cluster, continuing until there is one overall cluster.
Distances between objects are computed using a Distance.Function delegate. Delegates are provided as static variables on class Distance for euclidean, squared euclidean, city-block (Manhattan), maximum (Chebychev), and power distance functions. You can also create your own distance function delegate. Property Distances gets the vector of distances between all possible object pairs, computed using the current distance delegate.
Distances between clusters of objects are computed using a Linkage.Function delegate. Delegates are provided as static variables on class Linkage for single, complete, unweighted average, weighted average, centroid, median, and Ward's linkage functions. Again, you can also create your own linkage function delegate. The Linkages property gets the complete hierarchical linkage tree, computed from Distances using the current linkage delegate.
The CutTree() method constructs a set of clusters by cutting the hierarchical linkage tree either at the specified height, or into the specified number of clusters.

// cluster 8 random vectors of length 3
DoubleMatrix data = new DoubleMatrix( 8, 3, new RandGenUniform() );
ClusterAnalysis ca = new ClusterAnalysis( data,
  Distance.SquaredEuclideanFunction, Linkage.CompleteFunction );
Console.WriteLine( ca.Distances );
Console.WriteLine( ca.Linkages );

// cut linkage tree to form 3 clusters
Console.WriteLine( ca.CutTree( 3 ) );

// cut linkage tree at height of 0.75
Console.WriteLine( ca.CutTree( 0.75 ) );