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A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability) - Softcover
Synopsis
A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field.
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- PublisherSpringer
- Publication date2013
- ISBN 10 146126877X
- ISBN 13 9781461268772
- BindingPaperback
- LanguageEnglish
- Number of pages653
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A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)
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A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)
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A Probabilistic Theory of Pattern Recognition
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A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)
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A Probabilistic Theory of Pattern Recognition
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Springer New York Nov 2013, 2013
ISBN 10: 146126877X
ISBN 13: 9781461268772
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and exercises to further the readers understanding. Both research workers and graduate students will benefit from this wide-ranging and up-to-date account of a fast- moving field. 660 pp. Englisch. Seller Inventory # 9781461268772
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A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability (31))
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Paperback. Condition: New. Special order direct from the distributor Softcover reprint of the original 1st ed. 1996. Seller Inventory # ING9781461268772
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A Probabilistic Theory of Pattern Recognition
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. A self-contained and coherent account of probabilistic techniques, covering: distance measures, kernel rules, nearest neighbour rules, Vapnik-Chervonenkis theory, parametric classification, and feature extraction. Each chapter concludes with problems and ex. Seller Inventory # 4189514
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A Probabilistic Theory of Pattern Recognition
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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Pattern recognition presents one of the most significant challenges for scientists and engineers, and many different approaches have been proposed. The aim of this book is to provide a self-contained account of probabilistic analysis of these approaches. The book includes a discussion of distance measures, nonparametric methods based on kernels or nearest neighbors, Vapnik-Chervonenkis theory, epsilon entropy, parametric classification, error estimation, free classifiers, and neural networks. Wherever possible, distribution-free properties and inequalities are derived. A substantial portion of the results or the analysis is new. Over 430 problems and exercises complement the material. Seller Inventory # 9781461268772
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A Probabilistic Theory of Pattern Recognition
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Springer-Verlag New York Inc., 2013
ISBN 10: 146126877X
ISBN 13: 9781461268772
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Paperback / softback. Condition: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 1027. Seller Inventory # C9781461268772
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A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability)
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Paperback. Condition: Brand New. reprint edition. 653 pages. 9.25x6.10x1.42 inches. In Stock. Seller Inventory # x-146126877X
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