Package elki.clustering.kmeans
Class SingleAssignmentKMeans<V extends NumberVector>
- java.lang.Object
-
- elki.clustering.kmeans.AbstractKMeans<V,KMeansModel>
-
- elki.clustering.kmeans.SingleAssignmentKMeans<V>
-
- Type Parameters:
V
- vector datatype
- All Implemented Interfaces:
Algorithm
,ClusteringAlgorithm<Clustering<KMeansModel>>
,KMeans<V,KMeansModel>
public class SingleAssignmentKMeans<V extends NumberVector> extends AbstractKMeans<V,KMeansModel>
Pseudo-k-means variations, that assigns each object to the nearest center.- Since:
- 0.7.0
- Author:
- Erich Schubert
-
-
Nested Class Summary
Nested Classes Modifier and Type Class Description protected static class
SingleAssignmentKMeans.Instance
Inner instance, storing state for a single data set.static class
SingleAssignmentKMeans.Par<V extends NumberVector>
Parameterization class.-
Nested classes/interfaces inherited from interface elki.Algorithm
Algorithm.Utils
-
-
Field Summary
Fields Modifier and Type Field Description private static Logging
LOG
The logger for this class.-
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 SingleAssignmentKMeans(NumberVectorDistance<? super V> distance, int k, KMeansInitialization initializer)
Constructor.
-
Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description protected Logging
getLogger()
Get the (STATIC) logger for this class.Clustering<KMeansModel>
run(Relation<V> relation)
Run the clustering algorithm.-
Methods inherited from class elki.clustering.kmeans.AbstractKMeans
getDistance, getInputTypeRestriction, 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 Logging LOG
The logger for this class.
-
-
Constructor Detail
-
SingleAssignmentKMeans
public SingleAssignmentKMeans(NumberVectorDistance<? super V> distance, int k, KMeansInitialization initializer)
Constructor.- Parameters:
distance
- distance functionk
- k parameterinitializer
- Initialization method
-
-
Method Detail
-
run
public Clustering<KMeansModel> run(Relation<V> relation)
Description copied from interface:KMeans
Run the clustering algorithm.- Parameters:
relation
- Relation to process.- Returns:
- Clustering result
-
getLogger
protected Logging getLogger()
Description copied from class:AbstractKMeans
Get the (STATIC) logger for this class.- Specified by:
getLogger
in classAbstractKMeans<V extends NumberVector,KMeansModel>
- Returns:
- the static logger
-
-