de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.initialization

Interface KMedoidsInitialization<V>

Type Parameters:

V - Object type

All Known Implementing Classes:

FarthestPointsInitialMeans, FarthestSumPointsInitialMeans, FirstKInitialMeans, KMeansPlusPlusInitialMeans, PAMInitialMeans, RandomlyChosenInitialMeans

public interface KMedoidsInitialization<V>

Interface for initializing K-Medoids. In contrast to k-means initializers, this initialization will only return members of the original data set.

Author:

Erich Schubert

Method Summary

Methods

Modifier and Type	Method and Description
DBIDs	chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super V> distanceFunction) Choose initial means

Method Detail

chooseInitialMedoids

DBIDs chooseInitialMedoids(int k,
                         DBIDs ids,
                         DistanceQuery<? super V> distanceFunction)

Choose initial means

Parameters:

k - Parameter k

ids - Candidate IDs.

distanceFunction - Distance function

Returns:

List of chosen means for k-means