Finding Groups in Data An Introduction to Cluster Analysis

by Kaufman, Leonard; Rousseeuw, Peter J.

• ISBN13: 9780471735786
• ISBN10: 0471735787
• Edition: 1st
• Format: Paperback
• Copyright: 2005-03-25
• Publisher: Wiley-Interscience

Summary

An introduction to the practical application of cluster analysis,Finding Groups in Data presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. The text discusses the main approaches to clustering and provides guidance in choosing between the available methods. It also discusses various types of data, including interval-scaled and binary variables as well as similarity data and explains how these can be transformed prior to clustering. With numerous exercises to aid learning,Finding Groups in Data provides an invaluable introduction to cluster analysis with an emphasis on methods that are both easy to use and modern.

Author Biography

LEONARD KAUFMAN, PhD, is affiliated with Vrije University in Brussels, Belgium.

PETER J. ROUSSEEUW, PhD, is a Professor in the Department of Mathematics and Computer Science at the University of Antwerp in Belgium.

Table of Contents

1. Introduction.

2. Partitioning Around Medoids (Program PAM).

3. Clustering large Applications (Program CLARA).

4. Fuzzy Analysis.

5. Agglomerative Nesting (Program AGNES).

6. Divisive Analysis (Program DIANA).

7. Monothetic Analysis (Program MONA).

Appendix 1. Implementation and Structure of the Programs.

Appendix 2. Running the Programs.

Appendix 3. Adapting the Programs to Your Needs.

Appendix 4. The Program CLUSPLOT.

References.

Author Index.

Subject Index.