Learning from Data: Concepts, Theory, and Methods - Couverture rigide

Cherkassky, Vladimir; Mulier, Filip M.

Couverture rigide

ISBN 10 : 0471681822 ISBN 13 : 9780471681823

Editeur : Wiley-IEEE Press, 2007

Synopsis

Learning from Data An interdisciplinary framework for learning methodologies, covering statistics, neural networks, and fuzzy logic, Learning from Data provides a unified treatment of the principles and methods for learning dependencies from data. Full description

A propos du livre

Quatrième de couverture

An interdisciplinary framework for learning methodologies now revised and updated

Learning from Data provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and pattern recognition can be applied showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science.

Since the first edition was published, the field of data–driven learning has experienced rapid growth. This Second Edition covers these developments with a completely revised chapter on support vector machines, a new chapter on noninductive inference and alternative learning formulations, and an in–depth discussion of the VC theoretical approach as it relates to other paradigms.

Complete with over one hundred illustrations, case studies, examples, and chapter summaries, Learning from Data accommodates both beginning and advanced graduate students in engineering, computer science, and statistics. It is also indispensable for researchers and practitioners in these areas who must understand the principles and methods for learning dependencies from data.

Revue de presse

"I think Learning From Data is a very valuable volume. I will recommend it to my graduate students." ( Journal of the American Statistical Association, March 2009)

"The broad spectrum of information it offers is beneficial to many field of research. The selection of topics is good, and I believe that many researchers and practioners will find this book useful." (Technometrics, May 2008)

"The authors have succeeded in summarizing some of the recent trends and future challenges in different learning methods, including enabling technologies and some interesting practical applications." (Computing Reviews, May 22, 2008)

"The authors have succeeded in summarizing some of the recent trends and future challenges in different learning methods, including enabling technologies and some interesting practical applications." ( Computing Reviews, May 22, 2008)

Détails de l'édition

• Éditeur: Wiley-IEEE Press
• Date d'édition: 2007
• ISBN 10: 0471681822
• ISBN 13: 9780471681823
• Reliure: Relié
• Langue: anglais
• Numéro d'édition: 2
• Nombre de pages: 560