Class KMedoidsKMedoidsInitialization<O>

  • All Implemented Interfaces:
    KMedoidsInitialization<O>

    @Title("K-medoids Initialization by K-medoids")
    @Description("Initialize k-medoids with k-medoids, usually a less expensive variant.")
    public class KMedoidsKMedoidsInitialization<O>
    extends java.lang.Object
    implements KMedoidsInitialization<O>
    Initialize k-medoids with k-medoids, for methods such as PAMSIL.
    This could also be used to initialize, e.g., PAM with CLARA.

    TODO: this could be made more useful by adding a sampling option.

    Since:
    0.8.0
    Author:
    Erich Schubert
    • Field Summary

      Fields 
      Modifier and Type Field Description
      private KMedoidsClustering<O> inner
      Inner k-medoids clustering to use.
    • Method Summary

      All Methods Instance Methods Concrete Methods 
      Modifier and Type Method Description
      elki.database.ids.DBIDs chooseInitialMedoids​(int k, elki.database.ids.DBIDs ids, elki.database.query.distance.DistanceQuery<? super O> distance)
      Choose initial means
      • Methods inherited from class java.lang.Object

        clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
    • Constructor Detail

      • KMedoidsKMedoidsInitialization

        public KMedoidsKMedoidsInitialization​(KMedoidsClustering<O> inner)
        Constructor.
        Parameters:
        inner - Inner clustering
    • Method Detail

      • chooseInitialMedoids

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