Free Download Cluster Analysis By Brian S. Everitt, Sabine Landau, Morven Leese, Daniel Stahl

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Cluster Analysis By Brian S. Everitt, Sabine Landau, Morven Leese, Daniel Stahl

Free Download Cluster Analysis By Brian S. Everitt, Sabine Landau, Morven Leese, Daniel Stahl

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Sales Rank: #194812 in Books
Published on: 2011-02-21
Original language: English
Number of items: 1
Dimensions: 9.25" h x .95" w x 6.38" l, 1.41 pounds
Binding: Hardcover
346 pages

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 20031001 ...this continues to be an excellent general introduction to an important and expanding topic. -- Short Book Reviews 20011101

From the Publisher
An accessible and practical introduction to clustering using a minimum of mathematics. This extensively revised edition contains detailed descriptions of the latest methods along with numerous examples and updated information on available software packages. Closing chapters provide suggestions which will be helpful in many situations when applying clustering or evaluating results.

From the Back Cover
Cluster Analysis: 5th Edition

Brian S. Everitt, Professor Emeritus, King's College, London, UK
Sabine Landau, Morven Leese and Daniel Stahl, Institute of Psychiatry, King's College London, UK

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 5th 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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