de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch

Class DiameterCriterion

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical.birch.DiameterCriterion

All Implemented Interfaces:

BIRCHAbsorptionCriterion

@Alias(value="D")
 @Reference(authors="T. Zhang, R. Ramakrishnan, M. Livny",
           title="BIRCH: An Efficient Data Clustering Method for Very Large Databases",
           booktitle="Proc. 1996 ACM SIGMOD International Conference on Management of Data",
           url="https://doi.org/10.1145/233269.233324",
           bibkey="DBLP:conf/sigmod/ZhangRL96")
public class DiameterCriterion
extends java.lang.Object
implements BIRCHAbsorptionCriterion

Average Radius (R) criterion.

References:

T. Zhang, R. Ramakrishnan, M. Livny
BIRCH: An Efficient Data Clustering Method for Very Large Databases
Proc. 1996 ACM SIGMOD International Conference on Management of Data

Since:

0.7.5

Author:

Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	DiameterCriterion.Parameterizer Parameterization class

Field Summary

Fields

Modifier and Type	Field and Description
static DiameterCriterion	STATIC Static instance.

Constructor Summary

Constructors

Constructor and Description
DiameterCriterion()

Method Summary

Modifier and Type	Method and Description
double	squaredCriterion(ClusteringFeature f1, ClusteringFeature f2) Quality when merging two CFs.
double	squaredCriterion(ClusteringFeature f1, NumberVector n) Quality of a CF when adding a data point

Methods inherited from class java.lang.Object

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

Field Detail

STATIC

public static final DiameterCriterion STATIC

Static instance.

Constructor Detail

DiameterCriterion

public DiameterCriterion()

Method Detail

squaredCriterion

public double squaredCriterion(ClusteringFeature f1,
                               NumberVector n)

Description copied from interface: BIRCHAbsorptionCriterion

Quality of a CF when adding a data point

Specified by:

squaredCriterion in interface BIRCHAbsorptionCriterion

Parameters:

f1 - Clustering feature

n - Data point

Returns:

Quality

squaredCriterion

public double squaredCriterion(ClusteringFeature f1,
                               ClusteringFeature f2)

Description copied from interface: BIRCHAbsorptionCriterion

Quality when merging two CFs.

Specified by:

squaredCriterion in interface BIRCHAbsorptionCriterion

Parameters:

f1 - First clustering feature

f2 - Second clustering feature

Returns:

Quality