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

Interface KMeansInitialization

All Known Implementing Classes:

AbstractKMeansInitialization, FarthestPointsInitialMeans, FarthestSumPointsInitialMeans, FirstKInitialMeans, KMeansPlusPlusInitialMeans, LABInitialMeans, OstrovskyInitialMeans, PAMInitialMeans, ParkInitialMeans, PredefinedInitialMeans, RandomlyChosenInitialMeans, RandomNormalGeneratedInitialMeans, RandomUniformGeneratedInitialMeans, SampleKMeansInitialization

public interface KMeansInitialization

Interface for initializing K-Means

Since:

0.5.0

Author:

Erich Schubert

Method Summary

Modifier and Type	Method and Description
double[][]	chooseInitialMeans(Database database, Relation<? extends NumberVector> relation, int k, NumberVectorDistanceFunction<?> distanceFunction) Choose initial means

Method Detail

chooseInitialMeans

double[][] chooseInitialMeans(Database database,
                              Relation<? extends NumberVector> relation,
                              int k,
                              NumberVectorDistanceFunction<?> distanceFunction)

Choose initial means

Parameters:

database - Database context

relation - Relation

k - Parameter k

distanceFunction - Distance function

Returns:

List of chosen means for k-means