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Author:   A.D. Gordon
Publisher:   Taylor & Francis Inc
Imprint:   Chapman & Hall/CRC
Edition:   2nd edition
Volume:   82
Dimensions:   Width: 15.20cm , Height: 1.80cm , Length: 22.90cm
Weight:   0.660kg
ISBN:  

9781584880134

ISBN 10:   1584880139
Pages:   268
Publication Date:   17 June 1999
Audience:   College/higher education ,  Professional and scholarly ,  Undergraduate ,  Postgraduate, Research & Scholarly
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Introduction Classification, Assignment, and Dissection Aims of Classification Stages in a Numerical Classification Data Sets Measures of Similarity and Dissimilarity Introduction Selected Measures of Similarity and Dissimilarity Some Difficulties Construction of Relevant Measures Partitions Partitioning Criteria Iterative Relocation Algorithms Mathematical Programming Other Partitioning Algorithms How Many Clusters? Links with Statistical Models Hierarchical Classifications Definitions and Representations Algorithms Choice of Clustering Strategy Consensus Trees More General Tree Models Other Clustering Procedures Fuzzy Clustering Constrained Classification Overlapping Classification Conceptual Clustering Classification of Symbolic Data Partitions of Partitions Graphical Representations Introduction Principal Coordinates Analysis Non-Metric Multidimensional Scaling Interactive Graphics and Self-Organizing Maps Biplots Cluster Validation and Description Introduction Cluster Validation Cluster Description References Author Index Subject Index

Reviews

This book provides an excellent and comprehensive overview of the classification literaturecontains a considerable amount of new materialall chapters of this book are a pleasure to readWhile the Preface states that the book's material have been used by honours students, in reality it can be used by statisticians and nonstatisticians alike. Indeed, anyone who has to deal with large multivariate sets of data will benefitIn all, this volume is a valuable and welcome addition to the literature. - Short Book Reviews of the ISI, April 2000 A statistician embarking on a classification analysis of a set of data is presented with a bewildering array of choicesHaving read this book, he or she will have an even wider methodological palette from which to choose. However, they should be better able to make informed choices. -The Statistician, Volume 49, Part 3 (2000) One of the attractive features of the book is that it illustrates the ideas by application to a variety of real data sets. Biometrics, Vol. 56, No. 3, September 2000 this book presents both a solid basis for understanding its content and an adequate synthesis of the current state of the discipline. -IEEE Engineering in Medicine and Biology, Auly/August/2002

"""This book provides an excellent and comprehensive overview of the classification literaturecontains a considerable amount of new materialall chapters of this book are a pleasure to readWhile the Preface states that the book's material have been used by honours students, in reality it can be used by statisticians and nonstatisticians alike. Indeed, anyone who has to deal with large multivariate sets of data will benefitIn all, this volume is a valuable and welcome addition to the literature."" - Short Book Reviews of the ISI, April 2000 ""A statistician embarking on a classification analysis of a set of data is presented with a bewildering array of choicesHaving read this book, he or she will have an even wider methodological palette from which to choose. However, they should be better able to make informed choices."" -The Statistician, Volume 49, Part 3 (2000) ""One of the attractive features of the book is that it illustrates the ideas by application to a variety of real data sets."" Biometrics, Vol. 56, No. 3, September 2000 ""this book presents both a solid basis for understanding its content and an adequate synthesis of the current state of the discipline."" -IEEE Engineering in Medicine and Biology, Auly/August/2002"

Author Information

Gordon, A.D.

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