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

In: Journal of Classification, 2013.

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

In: Journal of Classification, 2013.

Research output: Contribution to journalArticlepeer-review

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@article{4b6710fb3d0c4ab3b1dd129090b5f3d8,
title = "Ward's Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward's Criterion?",
abstract = "The Ward error sum of squares hierarchical clustering method has been very widely used since its rst 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 dierent 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.",
author = "Fionn Murtagh and Pierre Legendre",
year = "2013",
language = "English",
journal = "Journal of Classification",
issn = "0176-4268",
publisher = "Springer New York",

}

RIS

TY - JOUR

T1 - Ward's Hierarchical Agglomerative Clustering Method: Which Algorithms Implement Ward's Criterion?

AU - Murtagh, Fionn

AU - Legendre, Pierre

PY - 2013

Y1 - 2013

N2 - The Ward error sum of squares hierarchical clustering method has been very widely used since its rst 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 dierent 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.

AB - The Ward error sum of squares hierarchical clustering method has been very widely used since its rst 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 dierent 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.

M3 - Article

JO - Journal of Classification

JF - Journal of Classification

SN - 0176-4268

ER -