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Can I read Cluster Analysis, Fifth Edition (Wiley Series in Probability and Statistics) on EtoBox?

Cluster Analysis, Fifth Edition (Wiley Series in Probability and Statistics) by Brian S. Everitt, Dr Sabine Landau, Dr Morven Leese, Dr Daniel Stahl is a nonfiction available to read on EtoBox.

What is Cluster Analysis, Fifth Edition (Wiley Series in Probability and Statistics) about?

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 presen

Who reads Cluster Analysis, Fifth Edition (Wiley Series in Probability and Statistics)?

It is typically read by self-directed learners exploring a subject in depth.

Common subject areas: history, science, philosophy, social sciences.

Author
Brian S. Everitt, Dr Sabine Landau, Dr Morven Leese, Dr Daniel Stahl
Publisher
John Wiley & Sons, Incorporated
Published
2011
Language
EN
ISBN
9780470977811
Category
nonfiction
Subjects
Mathematics, Computer Science, Stem

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