Class SameSizeKMeans<V extends NumberVector>

  • Type Parameters:
    V - Vector type
    All Implemented Interfaces:
    Algorithm, ClusteringAlgorithm<Clustering<MeanModel>>, KMeans<V,​MeanModel>

    public class SameSizeKMeans<V extends NumberVector>
    extends AbstractKMeans<V,​MeanModel>
    K-means variation that produces equally sized clusters.

    Note that this is a rather obvious variation, and one cannot expect very good results from this algorithm. K-means already is quite primitive, and putting in the size constraint will likely not make the results much better (in particular, it will even less be able to make sense of outliers!)

    There is no reference for this algorithm. If you want to cite it, please cite the latest ELKI release as given on the ELKI web page:

    Erich Schubert