Package elki.index.tree.betula.distance

Class BIRCHAverageInterclusterDistance

java.lang.Object

elki.index.tree.betula.distance.BIRCHAverageInterclusterDistance

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 BIRCHAverageInterclusterDistance
extends java.lang.Object
implements CFDistance

Average intercluster distance.

Reference:

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

Since:

0.8.0

Author:

Erich Schubert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field	Description
static BIRCHAverageInterclusterDistance	STATIC	Static instance.

Constructor Summary

Constructors

Constructor	Description
BIRCHAverageInterclusterDistance()

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 BIRCHAverageInterclusterDistance STATIC

Static instance.

Constructor Detail

BIRCHAverageInterclusterDistance

public BIRCHAverageInterclusterDistance()

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