Cluster Analysis Fifth Edition Wiley Series in Probability and Statistics 5th Edition by Brian Everitt, Dr Sabine Landau, Dr Morven Leese, Dr Daniel Stahl ISBN 978-1119955917 1119955917
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Cluster Analysis Fifth Edition Wiley Series in Probability and Statistics 5th Edition by Brian S. Everitt, Dr Sabine Landau, Dr Morven Leese, Dr Daniel Stahl – Ebook PDF Instant Download/Delivery: 978-1119955917, 1119955917
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Product details:
ISBN 10: 1119955917
ISBN 13: 978-1119955917
Author: Brian S. Everitt, Dr Sabine Landau, Dr Morven Leese, Dr Daniel Stahl
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 fifth 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./li>
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.
Table of contents:
Chapter 1: An Introduction to classification and clustering
Chapter 2: Detecting clusters graphically
Chapter 3: Measurement of proximity
Chapter 4: Hierarchical clustering
Chapter 5: Optimization clustering techniques
Chapter 6: Finite mixture densities as models for cluster analysis
Chapter 7: Model-based cluster analysis for structured data
Chapter 8: Miscellaneous clustering methods
Chapter 9: Some final comments and guidelines
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Tags: Brian Everitt, Dr Sabine Landau, Dr Morven Leese, Dr Daniel Stahl, Cluster Analysis