Methods of Hierarchical Clustering

Murtagh, Fionn and Contreras, Pedro

(2011)

Murtagh, Fionn and Contreras, Pedro (2011) Methods of Hierarchical Clustering
In: Data Mining and Knowledge Discovery. Wiley-Interscience.

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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.

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This is a Submitted version
This version's date is: 2011
This item is not peer reviewed

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https://repository.royalholloway.ac.uk/items/41bb0968-808c-62d6-4576-cffbf1315b63/5/

Item TypeBook Item
TitleMethods of Hierarchical Clustering
AuthorsMurtagh, Fionn
Contreras, Pedro
Uncontrolled Keywordscs.IR, cs.CV, math.ST, stat.ML, stat.TH, 62H30, H.3.3; H.2.8; G.3
DepartmentsFaculty of Science\Computer Science

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Deposited by Research Information System (atira) on 03-Jul-2014 in Royal Holloway Research Online.Last modified on 03-Jul-2014

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Submitted.


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