Package elki.index.tree.betula.distance

Class BIRCHAverageIntraclusterDistance

java.lang.Object

elki.index.tree.betula.distance.BIRCHAverageIntraclusterDistance

All Implemented Interfaces:

CFDistance

@Priority(-100)
@Reference(authors="T. Zhang",
           title="Data Clustering for Very Large Datasets Plus Applications",
           booktitle="University of Wisconsin Madison, Technical Report #1355",
           url="ftp://ftp.cs.wisc.edu/pub/techreports/1997/TR1355.pdf",
           bibkey="tr/wisc/Zhang97")
public class BIRCHAverageIntraclusterDistance
extends java.lang.Object
implements CFDistance

Average intracluster distance.

Reference:

Data Clustering for Very Large Datasets Plus Applications
T. Zhang
Doctoral Dissertation, 1997.

Note: this distance did not work well in the original work, apparently.

Since:

0.8.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	BIRCHAverageIntraclusterDistance.Par	Parameterization class.

Field Summary

Fields

Modifier and Type	Field	Description
static BIRCHAverageIntraclusterDistance	STATIC	Static instance.

Constructor Summary

Constructors

Constructor	Description
BIRCHAverageIntraclusterDistance()

Method Summary

Modifier and Type	Method	Description
double	squaredDistance(NumberVector v, ClusterFeature ocf)	Distance of a vector to a clustering feature.
double	squaredDistance(ClusterFeature ocf1, ClusterFeature ocf2)	Distance between two clustering features.

Methods inherited from class java.lang.Object

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

Methods inherited from interface elki.index.tree.betula.distance.CFDistance

matSelfInit

Field Detail

STATIC

public static final BIRCHAverageIntraclusterDistance STATIC

Static instance.

Constructor Detail

BIRCHAverageIntraclusterDistance

public BIRCHAverageIntraclusterDistance()

Method Detail

squaredDistance

public double squaredDistance(NumberVector v,
                              ClusterFeature ocf)

Description copied from interface: CFDistance

Distance of a vector to a clustering feature.

Specified by:

squaredDistance in interface CFDistance

Parameters:

v - Vector

ocf - Clustering Feature

Returns:

Distance

squaredDistance

public double squaredDistance(ClusterFeature ocf1,
                              ClusterFeature ocf2)

Description copied from interface: CFDistance

Distance between two clustering features.

Specified by:

squaredDistance in interface CFDistance

Parameters:

ocf1 - First clustering feature

ocf2 - Second clustering feature

Returns:

Distance