Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion?

Fionn Murtagh, Pierre Legendre

Research output: Contribution to journalArticle

605 Citations (Scopus)

Abstract

The Ward error sum of squares hierarchical clustering method has been very widely used since its first description by Ward in a 1963 publication. It has also been generalized in various ways. Two algorithms are found in the literature and software, both announcing that they implement the Ward clustering method. When applied to the same distance matrix, they produce different results. One algorithm preserves Ward’s criterion, the other does not. Our survey work and case studies will be useful for all those involved in developing software for data analysis using Ward’s hierarchical clustering method.

LanguageEnglish
Pages274-295
Number of pages22
JournalJournal of Classification
Volume31
Issue number3
DOIs
Publication statusPublished - 18 Oct 2014
Externally publishedYes

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Hierarchical Clustering
Clustering Methods
Cluster Analysis
Software
Distance Matrix
Sum of squares
Publications
Data analysis
data analysis
Hierarchical clustering
software

Cite this

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Ward’s Hierarchical Agglomerative Clustering Method : Which Algorithms Implement Ward’s Criterion? / Murtagh, Fionn; Legendre, Pierre.

In: Journal of Classification, Vol. 31, No. 3, 18.10.2014, p. 274-295.

Research output: Contribution to journalArticle

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