2. Detecting Clusters Graphically

  1. Brian S. Everitt,
  2. Sabine Landau,
  3. Morven Leese and
  4. Daniel Stahl

Published Online: 25 JAN 2011

DOI: 10.1002/9780470977811.ch2

Cluster Analysis, 5th Edition

Cluster Analysis, 5th Edition

How to Cite

Everitt, B. S., Landau, S., Leese, M. and Stahl, D. (2011) Detecting Clusters Graphically, in Cluster Analysis, 5th Edition, John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470977811.ch2

Author Information

  1. King's College London, UK

Publication History

  1. Published Online: 25 JAN 2011
  2. Published Print: 7 JAN 2011

Book Series:

  1. Wiley Series in Probability and Statistics

Book Series Editors:

  1. Walter A. Shewhart and
  2. Samuel S. Wilks

ISBN Information

Print ISBN: 9780470749913

Online ISBN: 9780470977811

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Keywords:

  • bivariate marginal plots;
  • cluster structure;
  • graphical techniques;
  • multivariate data;
  • Scatterplot matrices;
  • trellis graphics

Summary

This chapter describes a number of relatively simple, static graphical techniques that are useful for providing evidence for or against possible cluster structure in the data. Most of the methods are based on an examination of either direct univariate or bivariate marginal plots of the multivariate data, or indirect one- or two-dimensional “views” of the data obtained from the application to the data of a suitable dimension reduction technique. Scatterplots and, to some extent, scatterplot matrices are more useful for exploring multivariate data for the presence of clusters when there are only a relatively small number of variables. The chapter deals with plotting data in some two-dimensional space using either the original variables, or derived variables constructed in some way so that a low-dimensional projection of the data is informative. Trellis graphics and the associated lattice graphics examine high-dimensional structure in data by means of one-, two- and three-dimensional graphs.

Controlled Vocabulary Terms

bivariate analysis; cluster analysis; graphical model; multivariate chart; Scatter plot