Package elki.clustering.kmedoids.initialization

Class GreedyG<O>

java.lang.Object

elki.clustering.kmedoids.initialization.GreedyG<O>

Type Parameters:

O - Object type for KMedoids initialization

All Implemented Interfaces:

KMedoidsInitialization<O>

@Reference(authors="M. Eug\u00e9nia Captivo",
           title="Fast primal and dual heuristics for the p-median location problem",
           booktitle="European Journal of Operational Research 52(1)",
           url="https://doi.org/10.1016/0377-2217(91)90336-T",
           bibkey="doi:10.1016/0377-2217(91)90336-T")
public class GreedyG<O>
extends java.lang.Object
implements KMedoidsInitialization<O>

Initialization method for k-medoids that combines the Greedy (PAM BUILD) with "alternate" refinement steps. After choosing a new medoid, all points are assigned to the nearest center, and the medoid of the resulting partitions is used.

Reference:

M. Eugénia Captivo
Fast primal and dual heuristics for the p-median location problem
European Journal of Operational Research 52(1)

Since:

0.8.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	GreedyG.Par<V>	Parameterization class.

Field Summary

Fields

Modifier and Type	Field	Description
private static Logging	LOG	Class logger.

Constructor Summary

Constructors

Constructor	Description
GreedyG()	Constructor.

Method Summary

Modifier and Type	Method	Description
DBIDs	chooseInitialMedoids(int k, DBIDs ids, DistanceQuery<? super O> distQ)	Choose initial means
static double	findMedoid(DBIDs ids, DistanceQuery<?> distQ, int j, DBIDArrayMIter miter, double bestm, WritableDoubleDataStore temp, WritableDoubleDataStore tempbest, WritableDoubleDataStore mindist)	Find the best medoid of a given fixed set.

Methods inherited from class java.lang.Object

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

Field Detail

LOG

private static final Logging LOG

Class logger.

Constructor Detail

GreedyG

public GreedyG()

Constructor.

Method Detail

chooseInitialMedoids

public DBIDs chooseInitialMedoids(int k,
                                  DBIDs ids,
                                  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

findMedoid

public static double findMedoid(DBIDs ids,
                                DistanceQuery<?> distQ,
                                int j,
                                DBIDArrayMIter miter,
                                double bestm,
                                WritableDoubleDataStore temp,
                                WritableDoubleDataStore tempbest,
                                WritableDoubleDataStore mindist)

Find the best medoid of a given fixed set.

Parameters:

j - Cluster number

ids - Object ids

distQ - Distance query

miter - Medoid iterator, pointing to the current medoid (modified)

bestm - Prior cost, of the current assignment

temp - Temporary storage for distances

tempbest - Second temporary storage for distances

mindist - Minimum distance (output)

Returns:

New cost