Class EMProjectedClustering


  • public class EMProjectedClustering
    extends Object
    Implements clustering via Expectation Maximization but return a clear partitioning of the data, i.e. a point belongs to only one cluster (the most probable)
    Author:
    kranen
    • Constructor Detail

      • EMProjectedClustering

        public EMProjectedClustering()
    • Method Detail

      • getEMClusteringVariances

        public int[][] getEMClusteringVariances​(double[][] pointArray,
                                                int k)
        Performs an EM clustering on the provided data set !! Only the variances are calculated and used for point assignments ! !!! the number k' of returned clusters might be smaller than k !!!
        Parameters:
        pointArray - the data set as an array[n][d] of n points with d dimensions
        k - the number of requested partitions (!might return less)
        Returns:
        a mapping int[n][k'] of the n given points to the k' resulting clusters
      • getEMClusteringVariancesBestChoice

        public int[][] getEMClusteringVariancesBestChoice​(double[][] pointArray,
                                                          int k,
                                                          int nrOfChoices)