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Cluster Analysis

  • Brian Sidney Everitt
Chapter
  • 6.4k Downloads
Part of the Springer Texts in Statistics book series (STS)

Abstract

Cluster analysis is a generic term for a wide range of numerical methods for examin- ing multivariate data with a view to uncovering or discovering groups or clusters of observations that are homogeneous and separated from other groups. In medicine, for example, discovering that a sample of patients with measurements on a vari- ety of characteristics and symptoms actually consists of a small number of groups within which these characteristics are relatively similar, and between which they are different, might have important implications both in terms of future treatment and for investigating the aetiology of a condition. More recently cluster analysis techniques have been applied to microarray data (Alon et al., 1999) and image analysis (Everitt and Bullmore, 1999).

Keywords

Bayesian Information Criterion Complete Linkage Agglomerative Hierarchical Cluster Cluster Criterion Complete Linkage Cluster 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Limited 2005

Authors and Affiliations

  • Brian Sidney Everitt
    • 1
  1. 1.King’s CollegeLondonUK

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