de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans

Class KMeansAnnulus.Instance

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans.Instance

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansHamerly.Instance

de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansAnnulus.Instance

Enclosing class:

KMeansAnnulus<V extends NumberVector>

protected static class KMeansAnnulus.Instance
extends KMeansHamerly.Instance

Inner instance, storing state for a single data set.

Author:

Erich Schubert

Field Summary

Fields

Modifier and Type	Field and Description
(package private) double[]	cdist Cluster center distances.
(package private) int[]	cnum Sorted neighbors
(package private) WritableIntegerDataStore	second Second nearest cluster.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansHamerly.Instance

lower, newmeans, sep, sums, upper

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans.Instance

assignment, clusters, isSquared, k, key, means, relation, varsum

Constructor Summary

Constructors

Constructor and Description
Instance(Relation<? extends NumberVector> relation, NumberVectorDistanceFunction<?> df, double[][] means)

Method Summary

Modifier and Type	Method and Description
protected int	assignToNearestCluster() Reassign objects, but avoid unnecessary computations based on their bounds.
protected Logging	getLogger() Get the class logger.
protected int	initialAssignToNearestCluster() Perform initial cluster assignment.
protected void	orderMeans() Recompute the separation of cluster means.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansHamerly.Instance

iterate, recomputeSeperation, updateBounds

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.AbstractKMeans.Instance

buildResult, buildResult, copyMeans, distance, isSquared, meansFromSums, movedDistance, recomputeSeperation, run

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Field Detail

second

WritableIntegerDataStore second

Second nearest cluster.

cdist

double[] cdist

Cluster center distances.

cnum

int[] cnum

Sorted neighbors

Constructor Detail

Instance

public Instance(Relation<? extends NumberVector> relation,
                NumberVectorDistanceFunction<?> df,
                double[][] means)

Method Detail

initialAssignToNearestCluster

protected int initialAssignToNearestCluster()

Description copied from class: KMeansHamerly.Instance

Perform initial cluster assignment.

Overrides:

initialAssignToNearestCluster in class KMeansHamerly.Instance

Returns:

Number of changes (i.e. relation size)

orderMeans

protected void orderMeans()

Recompute the separation of cluster means.

assignToNearestCluster

protected int assignToNearestCluster()

Description copied from class: KMeansHamerly.Instance

Reassign objects, but avoid unnecessary computations based on their bounds.

Overrides:

assignToNearestCluster in class KMeansHamerly.Instance

Returns:

number of objects reassigned

getLogger

protected Logging getLogger()

Description copied from class: AbstractKMeans.Instance

Get the class logger.

Overrides:

getLogger in class KMeansHamerly.Instance

Returns:

Logger