Cluster Analysis [Hardcover]

Brian S. Everitt (Author), Dr Sabine Landau (Author), Dr Morven Leese (Author), Sabine Landau (Author), Morven Leese (Author)

Book Description

ISBN-10: 0340761199 | ISBN-13: 978-0340761199 | Publication Date: January 20, 2009 | Edition: 4th

Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organising multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques are applicable in a wide range of areas such as medicine, psychology and market research. This fourth edition of the highly successful Cluster Analysis represents a thorough revision of the third edition and covers new and developing areas such as classification likelihood and neural networks for clustering. Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. The book is comprehensive yet relatively non-mathematical, focusing on the practical aspects of cluster analysis.

Editorial Reviews

Review

... well structured and informative, providing detailed accounts of the new developments in the field. It is undoubtedly both an excellent inroduction to and a valuable reference work on cluster analysis. -- Swiss Journal of Psychology 20031001 ...this continues to be an excellent general introduction to an important and expanding topic. -- Short Book Reviews 20011101

From the Publisher

An accessible and practical introduction to clustering using a minimum of mathematics. This extensively revised edition contains detailed descriptions of the latest methods along with numerous examples and updated information on available software packages. Closing chapters provide suggestions which will be helpful in many situations when applying clustering or evaluating results. --This text refers to an out of print or unavailable edition of this title.

See all Editorial Reviews

Product Details

• Hardcover: 256 pages
• Publisher: Wiley; 4th edition (January 20, 2009)
• Language: English
• ISBN-10: 0340761199
• ISBN-13: 978-0340761199
• Product Dimensions: 9.4 x 6.1 x 0.7 inches
• Shipping Weight: 1.2 pounds
• Average Customer Review: 3.8 out of 5 stars  See all reviews (4 customer reviews)
• Amazon Best Sellers Rank: #1,744,560 in Books (See Top 100 in Books)

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Customer Reviews

Most Helpful Customer Reviews

13 of 15 people found the following review helpful:

4.0 out of 5 stars Good introduction, April 15, 2003

By A Customer

This review is from: Cluster Analysis (Hardcover)

Here is an excellent introduction to cluster analysis. The concepts are explained in clear language, with many illustrative examples. It is possibly the best of the introductory level books. I give it 4 stars because of a few misprints, and a few places where some essential information or detail has been omitted that can lead to misunderstanding.

3 of 3 people found the following review helpful:

3.0 out of 5 stars OK review of the field, February 25, 2008

By 

Maggiexyz - See all my reviews

This review is from: Cluster Analysis (Hardcover)

The book covered pretty extensively what's going on in the field of cluster analysis. It's a good reference book, but not the best in terms of teaching me the logic underlying various decisions in cluster analysis.

2 of 3 people found the following review helpful:

4.0 out of 5 stars Put SPSS Options in Context, March 22, 2008

By 

Keith McCormick (North Carolina, USA) - See all my reviews
(REAL NAME)   

Amazon Verified Purchase

This review is from: Cluster Analysis (Hardcover)

I'm a frequent user of SPSS software, including cluster analysis, and I found that I couldn't get good definitions of all the options available. I chose this book because I jotted down the terms that were poorly described in SPSS help, and then looked them up in the index of this book in the book description. I found several, so I bought the book.

I was pleased with the result. It put cluster in a much broader context than SPSS classes or user's guides do. It talks about techniques that SPSS can't do. If obviously goes into greater detail including more than a few formulas, but it reads fairly well. I still don't think that more than a handful of the folks I work with in need this much detail, and a serious practitioner might need even more. Kachigan's chapter on this topic would be more relevant to a wide audience. Multivariate Statistical Analysis: A Conceptual Introduction

Note that you won't find any explicit references except for an appendix which lists stats software and the related cluster features. This part is quite out of date. There are no SPSS pictures or examples. Still, if you want the whole story, this is a fine choice.