Cluster Analysis
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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 )
...this continues to be an excellent general introduction to an important and expanding topic. (Short Book Reviews ) --This text refers to an out of print or unavailable edition of this title.
...this continues to be an excellent general introduction to an important and expanding topic. (Short Book Reviews ) --This text refers to an out of print or unavailable edition of this title.
Product Description
Cluster analysis comprises a range of methods for classifying multivariate data into subgroups. By organizing multivariate data into such subgroups, clustering can help reveal the characteristics of any structure or patterns present. These techniques have proven useful in a wide range of areas such as medicine, psychology, market research and bioinformatics.
This fifth edition of the highly successful Cluster Analysis includes coverage of the latest developments in the field and a new chapter dealing with finite mixture models for structured data.
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.
Key Features:
• Presents a comprehensive guide to clustering techniques, with focus on the practical aspects of cluster analysis.
• Provides a thorough revision of the fourth edition, including new developments in clustering longitudinal data and examples from bioinformatics and gene studies
• Updates the chapter on mixture models to include recent developments and presents a new chapter on mixture modeling for structured data.
Practitioners and researchers working in cluster analysis and data analysis will benefit from this book.
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4 reviews
13 of 15 people found the following review helpful
Good introduction
15 April 2003
Format: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
OK review of the field
26 Feb 2008
Format: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
Put SPSS Options in Context
22 Mar 2008
Format:Hardcover|Amazon Verified Purchase
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.
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.
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