Kaufman / Rousseeuw Finding Groups in Data

An Introduction to Cluster Analysis
99. Auflage 2009
ISBN: 978-0-470-31748-8
Verlag: John Wiley & Sons
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 368 Seiten, E-Book

Reihe: Wiley Series in Probability and Statistics

The Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists.
"Cluster analysis is the increasingly important and practicalsubject of finding groupings in data. The authors set out to writea book for the user who does not necessarily have an extensivebackground in mathematics. They succeed very well."
--Mathematical Reviews
"Finding Groups in Data [is] a clear, readable, and interestingpresentation of a small number of clustering methods. In addition,the book introduced some interesting innovations of applied valueto clustering literature."
--Journal of Classification
"This is a very good, easy-to-read, and practical book. It hasmany nice features and is highly recommended for students andpractitioners in various fields of study."
--Technometrics
An introduction to the practical application of clusteranalysis, this text presents a selection of methods that togethercan deal with most applications. These methods are chosen for theirrobustness, consistency, and general applicability. This bookdiscusses various types of data, including interval-scaled andbinary variables as well as similarity data, and explains how thesecan be transformed prior to clustering.

Autoren/Hrsg.

Kaufman, Leonard

Rousseeuw, Peter J.

Inhaltsverzeichnis

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.

Über Autor(innen)

LEONARD KAUFMAN, PhD, is affiliated with Vrije University inBrussels, Belgium.
PETER J. ROUSSEEUW, PhD, is a Professor in the Department ofMathematics and Computer Science at the University of Antwerp inBelgium.