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Cluster analysis / Brian S. Everitt [and others].

Contributor(s): Everitt, BrianMaterial type: TextTextSeries: Wiley series in probability and statistics: Publisher: Chichester, West Sussex, U.K. : Wiley, 2011Edition: 5th edDescription: xii, 330 pages : illustrations ; 24 cmISBN: 9780470749913; 0470749911Subject(s): Cluster Analysis | Multivariate Analysis | MATHEMATICS -- Probability & Statistics -- Multivariate Analysis | Cluster-Analyse | Clusteranalyse | KlusteranalysDDC classification: 519.53 LOC classification: QA278 | .E9 2011Online resources: View this book online, via DawsonERA, both on- and off-campus | Cover image
Contents:
An introduction to classification and clustering -- Detecting clusters graphically -- Measurement of proximity -- Hierarchical clustering -- Optimization clustering techniques -- Finite mixture densities as models for cluster analysis -- Model-based cluster analysis for structured data -- Miscellaneous clustering methods -- Some final comments and guidelines.
Summary: "This edition provides a thorough revision of the fourth edition which focuses on the practical aspects of cluster analysis and covers new methodology in terms of longitudinal data and provides examples from bioinformatics. Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. This book includes an appendix of getting started on cluster analysis using R, as well as a comprehensive and up-to-date bibliography."--Summary: "This edition provides a thorough revision of the fourth edition which focuses on the practical aspects of cluster analysis and covers new methodology in terms of longitudinal data and provides examples from bioinformatics"--
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Reference Reference GKVK Library
519.53 EVE (Browse shelf) Not for loan 133983

Includes bibliographical references (pages 289-320) and index.

An introduction to classification and clustering -- Detecting clusters graphically -- Measurement of proximity -- Hierarchical clustering -- Optimization clustering techniques -- Finite mixture densities as models for cluster analysis -- Model-based cluster analysis for structured data -- Miscellaneous clustering methods -- Some final comments and guidelines.

"This edition provides a thorough revision of the fourth edition which focuses on the practical aspects of cluster analysis and covers new methodology in terms of longitudinal data and provides examples from bioinformatics. Real life examples are used throughout to demonstrate the application of the theory, and figures are used extensively to illustrate graphical techniques. This book includes an appendix of getting started on cluster analysis using R, as well as a comprehensive and up-to-date bibliography."--

"This edition provides a thorough revision of the fourth edition which focuses on the practical aspects of cluster analysis and covers new methodology in terms of longitudinal data and provides examples from bioinformatics"--

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