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portada Finding Groups in Data: An Introduction to Cluster Analysis (Paperback)
Type
Physical Book
Publisher
Author
Language
English
Pages
342
Format
Paperback
Weight
1
ISBN
0471735787
ISBN13
9780471735786
Edition No.
1
Categories

Finding Groups in Data: An Introduction to Cluster Analysis (Paperback)

Peter J. Rousseeuw Leonard Kaufman (Author) · John Wiley and Sons Ltd, United States · Paperback

Finding Groups in Data: An Introduction to Cluster Analysis (Paperback) - Peter J. Rousseeuw Leonard Kaufman

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Synopsis "Finding Groups in Data: An Introduction to Cluster Analysis (Paperback) "

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."—TechnometricsAn 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.

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