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

java.lang.Object
- elki.clustering.kmeans.AbstractKMeans<V,KMeansModel>
- - elki.clustering.kmeans.parallel.ParallelLloydKMeans<V>

Type Parameters:

V - Vector type

All Implemented Interfaces:

elki.Algorithm, ClusteringAlgorithm<Clustering<KMeansModel>>, KMeans<V,KMeansModel>
```
public class ParallelLloydKMeans<V extends elki.data.NumberVector>
extends AbstractKMeans<V,KMeansModel>
```
Parallel implementation of k-Means clustering.

Since:

0.7.0

Author:

Erich Schubert

Nested Class Summary
- Nested classes/interfaces inherited from class elki.clustering.kmeans.AbstractKMeans
  AbstractKMeans.Instance
- 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
Class logger
- Fields inherited from class elki.clustering.kmeans.AbstractKMeans
  distance, initializer, k, maxiter
- Fields inherited from interface elki.clustering.kmeans.KMeans
  DISTANCE_FUNCTION_ID, INIT_ID, K_ID, MAXITER_ID, SEED_ID, VARSTAT_ID

Constructor Summary

Constructors
Constructor	Description
`ParallelLloydKMeans(elki.distance.NumberVectorDistance<? super V> distance, int k, int maxiter, KMeansInitialization initializer)`	Constructor.

Method Summary

All Methods Instance Methods Concrete Methods
Modifier and Type	Method	Description
`elki.data.type.TypeInformation[]`	`getInputTypeRestriction()`
`protected elki.logging.Logging`	`getLogger()`	Get the (STATIC) logger for this class.
`Clustering<KMeansModel>`	`run(elki.database.relation.Relation<V> relation)`	Run the clustering algorithm.

Methods inherited from class elki.clustering.kmeans.AbstractKMeans
getDistance, incrementalUpdateMean, initialMeans, means, minusEquals, nearestMeans, plusEquals, plusMinusEquals, setDistance, setInitializer, setK

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
```
    Class logger
- Constructor Detail
  - ParallelLloydKMeans
```
public ParallelLloydKMeans(elki.distance.NumberVectorDistance<? super V> distance,
                           int k,
                           int maxiter,
                           KMeansInitialization initializer)
```
    Constructor.
    
    Parameters:
    
    distance - Distance function
    
    k - K parameter
- Method Detail
  - getInputTypeRestriction
```
public elki.data.type.TypeInformation[] getInputTypeRestriction()
```
    Specified by:
    
    getInputTypeRestriction in interface elki.Algorithm
    
    Overrides:
    
    getInputTypeRestriction in class AbstractKMeans<V extends elki.data.NumberVector,KMeansModel>
  - run
```
public Clustering<KMeansModel> run(elki.database.relation.Relation<V> relation)
```
    Description copied from interface: KMeans
    
    Run the clustering algorithm.
    
    Parameters:
    
    relation - Relation to process.
    
    Returns:
    
    Clustering result
  - getLogger
```
protected elki.logging.Logging getLogger()
```
    Description copied from class: AbstractKMeans
    
    Get the (STATIC) logger for this class.
    
    Specified by:
    
    getLogger in class AbstractKMeans<V extends elki.data.NumberVector,KMeansModel>
    
    Returns:
    
    the static logger