Chapter 13. Validation of Clustering Structure: Determination of the Number of Clusters
- Edwin Diday2,
- Monique Noirhomme-Fraiture3
Published Online: 28 JAN 2008
DOI: 10.1002/9780470723562.ch13
Copyright © 2008 John Wiley & Sons, Ltd
Book Title
Symbolic Data Analysis and the SODAS Software
Additional Information
How to Cite
Hardy, A. (2008) Validation of Clustering Structure: Determination of the Number of Clusters, in Symbolic Data Analysis and the SODAS Software (eds E. Diday and M. Noirhomme-Fraiture), John Wiley & Sons, Ltd, Chichester, UK. doi: 10.1002/9780470723562.ch13
Editor Information
- 2
Université Paris IX-Dauphine, LISE-CEREMADE, Place du Marechal de Lattre de Tassigny, Paris Cedex 16, France F-75775
- 3
Facultés Universitaires Notre-Dame de la Paix, Faculté d'Informatique, Rue Grandgagnage, 21, Namur, Belgium, B-5000
Publication History
- Published Online: 28 JAN 2008
- Published Print: 18 JAN 2007
ISBN Information
Print ISBN: 9780470018835
Online ISBN: 9780470723562
- Summary
- Chapter
Keywords:
- hypervolumes clustering criterion;
- interval-valued, multi-valued and modal variables;
- within-cluster pairwise dissimilarities and between-clusters pairwise dissimilarities;
- categorical multi-valued, quantitative multi-valued and interval-valued;
- dynamical clustering method;
- single linkage method;
- complete linkage method;
- centroid method and Ward method;
- hypervolumes clustering method;
- multidimensional Lebesgue measure
Summary
This chapter contains sections titled:
Introduction
The clustering problem
Classical criteria for the number of clusters
Symbolic variables
Dissimilarity measures for symbolic objects
Symbolic clustering procedures
Determination of the number of clusters for symbolic objects
Statistical models based on the Poisson processes
Statistical tests for the number of clusters based on the homogeneous Poisson point process
Examples
Conclusion
References