SingleAssignmentKMedoids (ELKI: Environment for DeveLoping KDD-Applications Supported by Index-Structures)

java.lang.Object
- elki.clustering.kmedoids.PAM<O>
- - elki.clustering.kmedoids.SingleAssignmentKMedoids<O>

Type Parameters:

O - object datatype

All Implemented Interfaces:

elki.Algorithm, ClusteringAlgorithm<Clustering<MedoidModel>>, KMedoidsClustering<O>
```
@Priority(-100)
public class SingleAssignmentKMedoids<O>
extends PAM<O>
```
K-medoids clustering by using the initialization only, then assigning each object to the nearest neighbor.

Since:

0.8.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes
Modifier and Type	Class	Description
`protected static class`	`SingleAssignmentKMedoids.Instance`	Instance for a single dataset.
`static class`	`SingleAssignmentKMedoids.Par<O>`	Parameterization class.

Nested classes/interfaces inherited from interface elki.Algorithm
elki.Algorithm.Utils

Field Summary

Fields
Modifier and Type Field Description

private static elki.logging.Logging LOG
The logger for this class.
- Fields inherited from class elki.clustering.kmedoids.PAM
  distance, initializer, k, maxiter

Constructor Summary

Constructors
Constructor	Description
`SingleAssignmentKMedoids(elki.distance.Distance<? super O> distance, int k, KMedoidsInitialization<O> initializer)`	Constructor.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`protected elki.logging.Logging`	`getLogger()`	Get the static class logger.
`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 class elki.clustering.kmedoids.PAM
getInputTypeRestriction, initialMedoids, run, wrapResult

Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface elki.clustering.ClusteringAlgorithm
autorun

- Field Detail
  - LOG
```
private static final elki.logging.Logging LOG
```
    The logger for this class.
- Constructor Detail
  - SingleAssignmentKMedoids
```
public SingleAssignmentKMedoids(elki.distance.Distance<? super O> distance,
                                int k,
                                KMedoidsInitialization<O> initializer)
```
    Constructor.
    
    Parameters:
    
    distance - distance function
    
    k - k parameter
    
    initializer - Function to generate the initial means
- Method Detail
  - run
```
public Clustering<MedoidModel> run(elki.database.relation.Relation<O> relation,
                                   int k,
                                   elki.database.query.distance.DistanceQuery<? super O> distQ)
```
    Description copied from interface: KMedoidsClustering
    
    Run k-medoids clustering with a given distance query.
    Not a very elegant API, but needed for some types of nested k-medoids.
    
    Specified by:
    
    run in interface KMedoidsClustering<O>
    
    Overrides:
    
    run in class PAM<O>
    
    Parameters:
    
    relation - relation to use
    
    k - Number of clusters
    
    distQ - Distance query to use
    
    Returns:
    
    result
  - getLogger
```
protected elki.logging.Logging getLogger()
```
    Description copied from class: PAM
    
    Get the static class logger.
    
    Overrides:
    
    getLogger in class PAM<O>