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

Murtagh, Fionn. 2014. Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion? Journal of Classification, 31(3), pp. 274-295. ISSN 0176-4268 [Article]

No full text available

Abstract or Description

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.

Item Type:

Article

Identification Number (DOI):

https://doi.org/10.1007/s00357-014-9161-z

Keywords:

Hierarchical clustering, Ward, Lance-Williams, Minimum variance, Statistical software

Departments, Centres and Research Units:

Computing

Dates:

DateEvent
18 October 2014Published

Item ID:

16194

Date Deposited:

11 Jan 2016 12:29

Last Modified:

21 Apr 2021 15:44

Peer Reviewed:

Yes, this version has been peer-reviewed.

URI:

https://research.gold.ac.uk/id/eprint/16194

Edit Record Edit Record (login required)