MTU Cork Library Catalogue

Syndetics cover image
Image from Syndetics

Cluster analysis / Brian S. Everitt..

By: Everitt, Brian.
Material type: materialTypeLabelBookPublisher: London : New York : E. Arnold, Halsted Press, c1993Edition: 3rd ed.Description: viii, 170 p. : ill. ; 24 cm. + hbk.ISBN: 0340584793; 0470220430.Subject(s): Cluster analysisDDC classification: 519.53
Contents:
An introduction to classification and clustering -- The initial examination of multivariate data -- Measurement of similarity, dissimilarity and distance -- Hierarchical clustering techniques -- Optimization methods for cluster analysis -- Mixture models for cluster analysis -- Other clustering techniques -- Some final comments and guidelines.
Holdings
Item type Current library Call number Copy number Status Date due Barcode Item holds
General Lending MTU Bishopstown Library Lending 519.53 (Browse shelf(Opens below)) 1 Available 00018873
Total holds: 0

Enhanced descriptions from Syndetics:

This practical text has been reworked to provide an account of the subject of cluster analysis - the generic name for a wide variety of procedures involved with identifying groups within data. By organizing multivariate data into such subgroups clustering may help the investigator discover the characteristics of any structure or pattern present. However, applying the methods in practice requires considerable care and researchers may need guidance in order to avoid misinterpreting results.

Includes bibliographical references (pages 155-164) and index.

An introduction to classification and clustering -- The initial examination of multivariate data -- Measurement of similarity, dissimilarity and distance -- Hierarchical clustering techniques -- Optimization methods for cluster analysis -- Mixture models for cluster analysis -- Other clustering techniques -- Some final comments and guidelines.

Table of contents provided by Syndetics

  • Preface
  • 1 An Introduction to Classification and Clustering
  • 2 The Initial Examination of Multivariate Data
  • 3 Measurement of Similarity, Dissimilarity and Distance
  • 4 Hierarchical Clustering Techniques
  • 5 Optimization Methods for Cluster Analysis
  • 6 Mixture Models for Cluster Analysis
  • 7 Other Clustering Techniques
  • 8 Some Final Comments and Guidelines
  • Appendix A Software
  • References
  • Index

Powered by Koha