Package elki.index.tree.betula.distance

Class RadiusDistance

java.lang.Object

elki.index.tree.betula.distance.RadiusDistance

All Implemented Interfaces:

CFDistance

@Alias("R")
@Reference(authors="Andreas Lang and Erich Schubert",title="BETULA: Numerically Stable CF-Trees for BIRCH Clustering",booktitle="Int. Conf on Similarity Search and Applications",url="https://doi.org/10.1007/978-3-030-60936-8_22",bibkey="DBLP:conf/sisap/LangS20") @Reference(authors="Andreas Lang and Erich Schubert",title="BETULA: Fast Clustering of Large Data with Improved BIRCH CF-Trees",booktitle="Information Systems",url="https://doi.org/10.1016/j.is.2021.101918",bibkey="DBLP:journals/is/LangS22")
public class RadiusDistance
extends java.lang.Object
implements CFDistance

Average Radius (R) criterion.

References:

Andreas Lang and Erich Schubert
BETULA: Numerically Stable CF-Trees for BIRCH Clustering
Int. Conf on Similarity Search and Applications 2020

Andreas Lang and Erich Schubert
BETULA: Fast Clustering of Large Data with Improved BIRCH CF-Trees
Information Systems

Since:

0.8.0

Author:

Andreas Lang, Erich Schubert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field	Description
static RadiusDistance	STATIC	Static instance.

Constructor Summary

Constructors

Constructor	Description
RadiusDistance()

Method Summary

Modifier and Type	Method	Description
double	matSelfInit(ClusterFeature cf)	Initialization for self measure for new Combinatorial clustering Methods (Podani 1989)
double	squaredDistance(NumberVector nv, ClusterFeature cf1)	Distance of a vector to a clustering feature.
double	squaredDistance(ClusterFeature cf1, ClusterFeature cf2)	Distance between two clustering features.

Methods inherited from class java.lang.Object

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

Field Detail

STATIC

public static final RadiusDistance STATIC

Static instance.

Constructor Detail

RadiusDistance

public RadiusDistance()

Method Detail

squaredDistance

public double squaredDistance(NumberVector nv,
                              ClusterFeature cf1)

Description copied from interface: CFDistance

Distance of a vector to a clustering feature.

Specified by:

squaredDistance in interface CFDistance

Parameters:

nv - Vector

cf1 - Clustering Feature

Returns:

Distance

squaredDistance

public double squaredDistance(ClusterFeature cf1,
                              ClusterFeature cf2)

Description copied from interface: CFDistance

Distance between two clustering features.

Specified by:

squaredDistance in interface CFDistance

Parameters:

cf1 - First clustering feature

cf2 - Second clustering feature

Returns:

Distance

matSelfInit

public double matSelfInit(ClusterFeature cf)

Description copied from interface: CFDistance

Initialization for self measure for new Combinatorial clustering Methods (Podani 1989)

Specified by:

matSelfInit in interface CFDistance

Parameters:

cf - Clustering Feature

Returns:

internal measure