Methods of Hierarchical Clustering

Fionn Murtagh, Pedro Contreras

Research output: Chapter in Book/Report/Conference proceedingChapter

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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 languageUndefined/Unknown
Title of host publicationData Mining and Knowledge Discovery
Publication statusPublished - 2011


  • cs.IR
  • cs.CV
  • math.ST
  • stat.ML
  • stat.TH
  • 62H30
  • H.3.3; H.2.8; G.3

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