Package elki.clustering.kmedoids

Interface KMedoidsClustering<O>

All Superinterfaces:

elki.Algorithm, ClusteringAlgorithm<Clustering<MedoidModel>>

All Known Implementing Classes:

AlternatingKMedoids, CLARA, CLARANS, EagerPAM, FastCLARA, FastCLARANS, FasterCLARA, FasterMSC, FasterPAM, FastMSC, FastPAM, FastPAM1, PAM, PAMMEDSIL, PAMSIL, ReynoldsPAM, SingleAssignmentKMedoids

public interface KMedoidsClustering<O>
extends ClusteringAlgorithm<Clustering<MedoidModel>>

Interface for clustering algorithms that produce medoids.

These may be used to initialize PAMSIL clustering, for example.

Since:

0.8.0

Author:

Erich Schubert

Nested Class Summary

Nested classes/interfaces inherited from interface elki.Algorithm

elki.Algorithm.Utils

Method Summary

Modifier and Type	Method	Description
Clustering<MedoidModel>	run(elki.database.relation.Relation<O> relation)	Run k-medoids clustering.
Clustering<MedoidModel>	run(elki.database.relation.Relation<O> relation, int k, elki.database.query.distance.DistanceQuery<? super O> distQ)	Run k-medoids clustering with a given distance query. Not a very elegant API, but needed for some types of nested k-medoids.

Methods inherited from interface elki.Algorithm

getInputTypeRestriction

Methods inherited from interface elki.clustering.ClusteringAlgorithm

autorun

Method Detail

run

Clustering<MedoidModel> run(elki.database.relation.Relation<O> relation)

Run k-medoids clustering.

Parameters:

relation - relation to use

Returns:

result

run

Clustering<MedoidModel> run(elki.database.relation.Relation<O> relation,
                            int k,
                            elki.database.query.distance.DistanceQuery<? super O> distQ)

Run k-medoids clustering with a given distance query.
Not a very elegant API, but needed for some types of nested k-medoids.

Parameters:

relation - relation to use

k - Number of clusters

distQ - Distance query to use

Returns:

result