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Cluster Analysis / Brian S. Everitt.

By: Contributor(s): Material type: TextTextSeries: Wiley series in probability and statisticsPublication details: Hoboken : Wiley, 2011.Edition: 5th edDescription: 1 online resource (xii, 330 pages) : illustrationsContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9780470977811
  • 0470977817
  • 9780470977804
  • 0470977809
  • 0470978449
  • 9780470978443
  • 0470749911
  • 9780470749913
Subject(s): Genre/Form: Additional physical formats: Print version:: Cluster Analysis.DDC classification:
  • 519.5/3 22
LOC classification:
  • QA278 .E9 2011
Other classification:
  • 31.73
Online resources:
Contents:
Front Matter -- 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 -- Bibliography -- Index.
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."-- Provided by publisher.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"-- Provided by publisher.
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Front Matter -- 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 -- Bibliography -- Index.

"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."-- Provided by publisher.

"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"-- Provided by publisher.

Includes bibliographical references and index.

Print version record.

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