Package elki.clustering.hierarchical

Class MiniMax<O>

java.lang.Object

elki.clustering.hierarchical.MiniMax<O>

Type Parameters:

O - Object type

All Implemented Interfaces:

Algorithm, HierarchicalClusteringAlgorithm

Direct Known Subclasses:

MiniMaxAnderberg, MiniMaxNNChain

@Reference(authors="S. I. Ao, K. Yip, M. Ng, D. Cheung, P.-Y. Fong, I. Melhado, P. C. Sham",title="CLUSTAG: hierarchical clustering and graph methods for selecting tag SNPs",booktitle="Bioinformatics, 21 (8)",url="https://doi.org/10.1093/bioinformatics/bti201",bibkey="DBLP:journals/bioinformatics/AoYNCFMS05") @Reference(authors="J. Bien, R. Tibshirani",title="Hierarchical Clustering with Prototypes via Minimax Linkage",booktitle="Journal of the American Statistical Association 106(495)",url="https://doi.org/10.1198/jasa.2011.tm10183",bibkey="doi:10.1198/jasa.2011.tm10183")
public class MiniMax<O>
extends java.lang.Object
implements HierarchicalClusteringAlgorithm

Minimax Linkage clustering.

Reference:

S. I. Ao, K. Yip, M. Ng, D. Cheung, P.-Y. Fong, I. Melhado, P. C. Sham
CLUSTAG: hierarchical clustering and graph methods for selecting tag SNPs
Bioinformatics, 21 (8)

J. Bien and R. Tibshirani
Hierarchical Clustering with Prototypes via Minimax Linkage
Journal of the American Statistical Association 106(495)

Since:

0.7.5

Author:

Julian Erhard, Erich Schubert

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	MiniMax.Instance	Main worker instance of MiniMax.

Nested classes/interfaces inherited from interface elki.Algorithm

Algorithm.Utils

Field Summary

Fields

Modifier and Type	Field	Description
protected Distance<? super O>	distance	Distance function used.
private static Logging	LOG	Class Logger.

Constructor Summary

Constructors

Constructor	Description
MiniMax(Distance<? super O> distance)	Constructor.

Method Summary

Modifier and Type	Method	Description
TypeInformation[]	getInputTypeRestriction()	Get the input type restriction used for negotiating the data query.
protected static <O> ClusterDistanceMatrix	initializeMatrices(ArrayDBIDs ids, ArrayModifiableDBIDs prots, DistanceQuery<O> dq)	Initializes the inter-cluster distance matrix of possible merges
ClusterPrototypeMergeHistory	run(Relation<O> relation)	Run the algorithm on a database.

Methods inherited from class java.lang.Object

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

Methods inherited from interface elki.clustering.hierarchical.HierarchicalClusteringAlgorithm

autorun

Field Detail

LOG

private static final Logging LOG

Class Logger.

distance

protected Distance<? super O> distance

Distance function used.

Constructor Detail

MiniMax

public MiniMax(Distance<? super O> distance)

Constructor.

Parameters:

distance - Distance function to use.

Method Detail

getInputTypeRestriction

public TypeInformation[] getInputTypeRestriction()

Description copied from interface: Algorithm

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

Specified by:

getInputTypeRestriction in interface Algorithm

Returns:

Type restriction

run

public ClusterPrototypeMergeHistory run(Relation<O> relation)

Run the algorithm on a database.

Parameters:

relation - Relation to process.

Returns:

Hierarchical result

initializeMatrices

protected static <O> ClusterDistanceMatrix initializeMatrices(ArrayDBIDs ids,
                                                              ArrayModifiableDBIDs prots,
                                                              DistanceQuery<O> dq)

Initializes the inter-cluster distance matrix of possible merges

Parameters:

ids - Object ids

prots - Prototype storage

dq - The distance query

Returns:

mat Cluster distance matrix