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

Open access
Murtagh, Fionn, Legendre, Pierre·2014·Journal of Classification

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.

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Metadata

Authors
Murtagh, F., & Legendre, P.
Venue
Journal of Classification
Published
2014-10
Volume
31
Issue
3
Pages
274-295
ISSN
  • 0176-4268 (ISSN-L)
  • 1432-1343
OpenAlex
W2049017883
Cited by
3,782
References
1
FWCI
100.35
Type
journal article
Language
en
Open access
green

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Murtagh, F., & Legendre, P. (2014). Ward’s Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward’s Criterion? Journal of Classification. https://doi.org/10.1007/s00357-014-9161-z

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.