Package elki.clustering.kmedoids
Interface KMedoidsClustering<O>
-
- All Superinterfaces:
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
Algorithm.Utils
-
-
Method Summary
All Methods Instance Methods Abstract Methods Modifier and Type Method Description Clustering<MedoidModel>
run(Relation<O> relation)
Run k-medoids clustering.Clustering<MedoidModel>
run(Relation<O> relation, int k, 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(Relation<O> relation)
Run k-medoids clustering.- Parameters:
relation
- relation to use- Returns:
- result
-
run
Clustering<MedoidModel> run(Relation<O> relation, int k, 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 usek
- Number of clustersdistQ
- Distance query to use- Returns:
- result
-
-