KMeansClustering Class 
Namespace: CenterSpace.NMath.Core
The KMeansClustering type exposes the following members.
Name  Description  

KMeansClustering 
Constructs an empty KMeansClustering instance.
 
KMeansClustering(DataFrame) 
Constructs a KMeansClustering instance from the given data.
 
KMeansClustering(DoubleMatrix) 
Constructs a KMeansClustering instance from the given data.
 
KMeansClustering(DataFrame, Int32) 
Constructs a KMeansClustering instance from the given data and the
specified maximum number of iterations.
 
KMeansClustering(DoubleMatrix, Int32) 
Constructs a KMeansClustering instance from the given data and the
specified maximum number of iterations.

Name  Description  

Clusters 
Gets the cluster assignments computed during the last clustering.
 
Data 
Gets and sets the data matrix.
 
DefaultMaxIterations 
Gets and sets the default maximum number of iterations.
 
FinalCenters 
Gets the matrix of final cluster centers computed during the last clustering.
 
InitialCenters 
Gets the matrix of initial cluster centers used during the last clustering.
 
Iterations 
Gets the number of iterations used in the clustering just computed.
 
K 
Gets the number of clusters computed during the last clustering..
 
MaxIterations 
Gets and sets the maximum number of iterations used in clustering.
 
MaxIterationsMet 
Returns true if the clustering just computed stopped because the
maximum number of iterations was reached; otherwise, false.
 
N 
Gets the number of objects in this.Data.
 
Sizes 
Gets the number of points in each cluster computed during the last clustering.
 
WithinSumOfSquares 
Gets the withincluster sum of squares for each cluster computed during the last clustering.

Name  Description  

Clone 
Creates a deep copy of this cluster analysis.
 
Cluster(Int32) 
Clusters the data into the specified number of clusters.
 
Cluster(DoubleMatrix) 
Clusters the data into the specified number of clusters.
 
Cluster(Int32, KMeansClusteringStart) 
Clusters the data into the specified number of clusters, using the specified method of
choosing the initial cluster centers.
 
Cluster(Int32, RandGenMTwist) 
Clusters the data into the specified number of clusters.

Name  Description  

clusters_  The cluster assigments.  
data_ 
A matrix of data. Each row in the matrix represents an object to be clustered.
 
DEFAULT_MAX_ITER  The default maximum number of iterations.  
finalCenters_ 
A matrix of final cluster centers.
 
initialCenters_ 
A matrix of initial cluster centers.
 
iter_  The number of iterations performed.  
max_  The maximum number of iterations.  
sizes_ 
The number of objects in each cluster.
 
withinss_ 
The withincluster sum of squares for each cluster.

// cluster 8 random vectors of length 3 DoubleMatrix data = new DoubleMatrix( 8, 3, new RandGenUniform() ); KMeansClustering cl = new KMeansClustering( data ); // create 3 clusters, using random starting cluster centers ClusterSet clusters = cl.Cluster( 3 );