Finding Groups in Data: An Introduction to Cluster Analysis by Leonard Kaufman (

Description: Finding Groups in Data by Leonard Kaufman, Peter J. Rousseeuw 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. FORMAT Paperback LANGUAGE English CONDITION Brand New Publisher Description The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Cluster analysis is the increasingly important and practical subject of finding groupings in data. The authors set out to write a book for the user who does not necessarily have an extensive background in mathematics. They succeed very well."—Mathematical Reviews "Finding Groups in Data [is] a clear, readable, and interesting presentation of a small number of clustering methods. In addition, the book introduced some interesting innovations of applied value to clustering literature."—Journal of Classification "This is a very good, easy-to-read, and practical book. It has many nice features and is highly recommended for students and practitioners in various fields of study."—Technometrics An introduction to the practical application of cluster analysis, this text presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. This book 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. Back Cover The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Cluster analysis is the increasingly important and practical subject of finding groupings in data. The authors set out to write a book for the user who does not necessarily have an extensive background in mathematics. They succeed very well." —Mathematical Reviews "Finding Groups in Data [is] a clear, readable, and interesting presentation of a small number of clustering methods. In addition, the book introduced some interesting innovations of applied value to clustering literature." —Journal of Classification "This is a very good, easy-to-read, and practical book. It has many nice features and is highly recommended for students and practitioners in various fields of study." —Technometrics An introduction to the practical application of cluster analysis, this text presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. This book 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. Flap The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Cluster analysis is the increasingly important and practical subject of finding groupings in data. The authors set out to write a book for the user who does not necessarily have an extensive background in mathematics. They succeed very well." -- Mathematical Reviews "Finding Groups in Data [is] a clear, readable, and interesting presentation of a small number of clustering methods. In addition, the book introduced some interesting innovations of applied value to clustering literature." -- Journal of Classification "This is a very good, easy-to-read, and practical book. It has many nice features and is highly recommended for students and practitioners in various fields of study." -- Technometrics An introduction to the practical application of cluster analysis, this text presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. This book 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. 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. Long Description The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. "Cluster analysis is the increasingly important and practical subject of finding groupings in data. The authors set out to write a book for the user who does not necessarily have an extensive background in mathematics. They succeed very well." --Mathematical Reviews "Finding Groups in Data [is] a clear, readable, and interesting presentation of a small number of clustering methods. In addition, the book introduced some interesting innovations of applied value to clustering literature." --Journal of Classification "This is a very good, easy-to-read, and practical book. It has many nice features and is highly recommended for students and practitioners in various fields of study." --Technometrics An introduction to the practical application of cluster analysis, this text presents a selection of methods that together can deal with most applications. These methods are chosen for their robustness, consistency, and general applicability. This book 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. Details ISBN0471735787 Author Peter J. Rousseeuw Short Title FINDING GROUPS IN DATA Series Wiley Series in Probability and Statistics Language English ISBN-10 0471735787 ISBN-13 9780471735786 Media Book Format Paperback DEWEY 519.53 Year 2005 Edition 2nd Subtitle An Introduction to Cluster Analysis Place of Publication New York Country of Publication United States Replaces 9780471878766 DOI 10.1604/9780471735786 Series Number 603 UK Release Date 2005-05-03 AU Release Date 2005-03-11 NZ Release Date 2005-03-11 Pages 368 Publisher John Wiley & Sons Inc Publication Date 2005-05-03 Imprint Wiley-Interscience Alternative 9780471878766 Illustrations Graphs: 113 B&W, 0 Color Audience Professional & Vocational US Release Date 2005-05-03 We've got this At The Nile, if you're looking for it, we've got it. With fast shipping, low prices, friendly service and well over a million items - you're bound to find what you want, at a price you'll love! TheNile_Item_ID:102472379;

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