![]() | KMeans |
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 within-cluster sum of squares for each cluster computed during the last clustering. |
Name | Description | |
---|---|---|
![]() | Clone | Creates a deep copy of this cluster analysis. |
![]() | Cluster(DoubleMatrix) | Clusters the data into the specified number of clusters. |
![]() | Cluster(Int32) | 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 within-cluster 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 );