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

Class BIRCHLeafClustering

java.lang.Object

de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm<Clustering<MeanModel>>

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

All Implemented Interfaces:

Algorithm, ClusteringAlgorithm<Clustering<MeanModel>>

@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") @Reference(authors="T. Zhang, R. Ramakrishnan, M. Livny",title="BIRCH: A New Data Clustering Algorithm and Its Applications",booktitle="Data Min. Knowl. Discovery",url="https://doi.org/10.1023/A:1009783824328",bibkey="DBLP:journals/datamine/ZhangRL97")
public class BIRCHLeafClustering
extends AbstractAlgorithm<Clustering<MeanModel>>
implements ClusteringAlgorithm<Clustering<MeanModel>>

BIRCH-based clustering algorithm that simply treats the leafs of the CFTree as clusters.

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

T. Zhang, R. Ramakrishnan, M. Livny
BIRCH: A New Data Clustering Algorithm and Its Applications Data. Min. Knowl. Discovery

Since:

0.7.5

Author:

Erich Schubert

Nested Class Summary

Nested Classes

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

Field Summary

Fields

Modifier and Type	Field and Description
(package private) CFTree.Factory	cffactory CFTree factory.
private static Logging	LOG Class logger.

Fields inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

ALGORITHM_ID

Constructor Summary

Constructors

Constructor and Description
BIRCHLeafClustering(CFTree.Factory cffactory) Constructor.

Method Summary

Modifier and Type	Method and Description
TypeInformation[]	getInputTypeRestriction() Get the input type restriction used for negotiating the data query.
protected Logging	getLogger() Get the (STATIC) logger for this class.
Clustering<MeanModel>	run(Relation<NumberVector> relation) Run the clustering algorithm.

Methods inherited from class de.lmu.ifi.dbs.elki.algorithm.AbstractAlgorithm

run

Methods inherited from class java.lang.Object

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

Methods inherited from interface de.lmu.ifi.dbs.elki.algorithm.clustering.ClusteringAlgorithm

run

Field Detail

LOG

private static final Logging LOG

Class logger.

cffactory

CFTree.Factory cffactory

CFTree factory.

Constructor Detail

BIRCHLeafClustering

public BIRCHLeafClustering(CFTree.Factory cffactory)

Constructor.

Parameters:

cffactory - CFTree Factory

Method Detail

run

public Clustering<MeanModel> run(Relation<NumberVector> relation)

Run the clustering algorithm.

Parameters:

relation - Input data

Returns:

Clustering

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from class: AbstractAlgorithm

Get the input type restriction used for negotiating the data query.

Specified by:

getInputTypeRestriction in interface Algorithm

Specified by:

getInputTypeRestriction in class AbstractAlgorithm<Clustering<MeanModel>>

Returns:

Type restriction

getLogger

protected Logging getLogger()

Description copied from class: AbstractAlgorithm

Get the (STATIC) logger for this class.

Specified by:

getLogger in class AbstractAlgorithm<Clustering<MeanModel>>

Returns:

the static logger