Package elki.clustering.kmedoids.initialization

Class LAB<O>

  • Type Parameters:
    O - Object type for KMedoids initialization
    All Implemented Interfaces:
    KMeansInitialization, KMedoidsInitialization<O>
    @Reference(authors="Erich Schubert, Peter J. Rousseeuw",
           title="Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms",
           booktitle="Proc. 12th Int. Conf. Similarity Search and Applications (SISAP\'2019)",
           url="https://doi.org/10.1007/978-3-030-32047-8_16",
           bibkey="DBLP:conf/sisap/SchubertR19")
public class LAB<O>
extends java.lang.Object
implements KMeansInitialization, KMedoidsInitialization<O>
    Linear approximative BUILD (LAB) initialization for FastPAM (and k-means).

    This is a O(nk) aproximation of the original PAM BUILD. For performance, it uses an O(sqrt(n)) sample to achieve linear run time. The results will be worse than those of BUILD, but provide a good starting point for FastPAM optimization.

    Reference:

    Erich Schubert, Peter J. Rousseeuw
    Faster k-Medoids Clustering: Improving the PAM, CLARA, and CLARANS Algorithms
    Proc. 12th Int. Conf. Similarity Search and Applications (SISAP'2019)

    Since:
    0.7.5
    Author:
    Erich Schubert

    • Nested Class Summary

      Nested Classes 
      Modifier and Type Class Description
      static class  LAB.Par<V>
      Parameterization class.

    • Field Summary

      Fields 
      Modifier and Type Field Description
      private static elki.logging.Logging LOG
      Class logger.
      private elki.utilities.random.RandomFactory rnd
      Random generator

    • Constructor Summary

      Constructors 
      Constructor Description
      LAB​(elki.utilities.random.RandomFactory rnd)
      Constructor.

    • Method Summary

      All Methods Static Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      double[][] chooseInitialMeans​(elki.database.relation.Relation<? extends elki.data.NumberVector> relation, int k, elki.distance.NumberVectorDistance<?> distance)
      Choose initial means
      elki.database.ids.DBIDs chooseInitialMedoids​(int k, elki.database.ids.DBIDs ids, elki.database.query.distance.DistanceQuery<? super O> distQ)
      Choose initial means
      protected static double getMinDist​(elki.database.ids.DBIDArrayIter j, elki.database.query.distance.DistanceQuery<?> distQ, elki.database.ids.DBIDArrayIter mi, elki.database.datastore.WritableDoubleDataStore mindist)
      Get the minimum distance to previous medoids.
      private static void shuffle​(elki.database.ids.ArrayModifiableDBIDs ids, int ssize, int end, java.util.Random random)
      Partial Fisher-Yates shuffle.

      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    • Field Detail

      • LOG

        private static final elki.logging.Logging LOG
        Class logger.

      • rnd

        private elki.utilities.random.RandomFactory rnd
        Random generator

    • Constructor Detail

      • LAB

        public LAB​(elki.utilities.random.RandomFactory rnd)
        Constructor.
        Parameters:
        rnd - Random generator

    • Method Detail

      • chooseInitialMeans

        public double[][] chooseInitialMeans​(elki.database.relation.Relation<? extends elki.data.NumberVector> relation,
                                     int k,
                                     elki.distance.NumberVectorDistance<?> distance)
        Description copied from interface: KMeansInitialization
        Choose initial means
        Specified by:
        chooseInitialMeans in interface KMeansInitialization
        Parameters:
        relation - Relation
        k - Parameter k
        distance - Distance function
        Returns:
        List of chosen means for k-means

      • chooseInitialMedoids

        public elki.database.ids.DBIDs chooseInitialMedoids​(int k,
                                                    elki.database.ids.DBIDs ids,
                                                    elki.database.query.distance.DistanceQuery<? super O> distQ)
        Description copied from interface: KMedoidsInitialization
        Choose initial means
        Specified by:
        chooseInitialMedoids in interface KMedoidsInitialization<O>
        Parameters:
        k - Parameter k
        ids - Candidate IDs.
        distQ - Distance function
        Returns:
        List of chosen means for k-means

      • getMinDist

        protected static double getMinDist​(elki.database.ids.DBIDArrayIter j,
                                   elki.database.query.distance.DistanceQuery<?> distQ,
                                   elki.database.ids.DBIDArrayIter mi,
                                   elki.database.datastore.WritableDoubleDataStore mindist)
        Get the minimum distance to previous medoids.
        Parameters:
        j - current object
        distQ - distance query
        mi - medoid iterator
        mindist - distance storage
        Returns:
        minimum distance

      • shuffle

        private static void shuffle​(elki.database.ids.ArrayModifiableDBIDs ids,
                            int ssize,
                            int end,
                            java.util.Random random)
        Partial Fisher-Yates shuffle.
        Parameters:
        ids - IDs to shuffle
        ssize - sample size to generate
        end - Valid range
        random - Random generator