Algorithms for hierarchical clustering: An Overview

Fionn Murtagh, Pedro Contreras Albornoz

Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)


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.
Original languageEnglish
Title of host publicationData Mining and Knowledge Discovery, Wiley Interdisciplinary Reviews (WIRES)
PublisherJohn Wiley & Sons
Number of pages12
Publication statusPublished - 2011

Publication series

NameWiley Interdisciplinary Reviews

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