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Algorithms for Hierarchical Clustering: An Overview, II

Murtagh, Fionn and Contreras, Pedro (2017) Algorithms for Hierarchical Clustering: An Overview, II. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery. ISSN 1942-4795 (In Press)

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Abstract

We survey agglomerative hierarchical clustering algorithms and discuss efficient implementations that are available in R and other software environments. We look at hierarchical self-organizing maps, and mixture models. We review grid-based clustering, focusing on hierarchical density-based approaches. Finally we describe a recently developed very efficient (linear time) hierarchical clustering algorithm, which can also be viewed as a hierarchical grid-based algorithm. This review adds to the earlier version, Murtagh and Contreras (2012).

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Item Type: Article
Additional Information: Article ID: WIDM1219
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Z Bibliography. Library Science. Information Resources > ZA Information resources
Schools: School of Computing and Engineering
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Depositing User: Fionn Murtagh
Date Deposited: 09 Aug 2017 14:03
Last Modified: 10 Aug 2017 06:48
URI: http://eprints.hud.ac.uk/id/eprint/32552

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