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Pattern recognition presents a significant challege for scientists and engineers, and many different approaches have been proposed. This book provides a self-contained account of probabilistic techniques that have been applied to the subject. Researchers and graduate students will benefit from this wide-ranging account of the field.
Reseña del editor: 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.
Título: A Probabilistic Theory of Pattern ...
Editorial: Springer
Año de publicación: 2013
Encuadernación: paperback
Condición: Good
Librería: moluna, Greven, Alemania
Condición: 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. Nº de ref. del artículo: 4189514
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Librería: preigu, Osnabrück, Alemania
Taschenbuch. Condición: Neu. A Probabilistic Theory of Pattern Recognition | Luc Devroye (u. a.) | Taschenbuch | xv | Englisch | 2013 | Springer | EAN 9781461268772 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Nº de ref. del artículo: 105322850
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Librería: Lucky's Textbooks, Dallas, TX, Estados Unidos de America
Condición: New. Nº de ref. del artículo: ABLIING23Mar2716030028349
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Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
Taschenbuch. Condición: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 660 pp. Englisch. Nº de ref. del artículo: 9781461268772
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Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9781461268772
Cantidad disponible: 2 disponibles
Librería: Chiron Media, Wallingford, Reino Unido
Paperback. Condición: New. Nº de ref. del artículo: 6666-IUK-9781461268772
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Librería: AHA-BUCH GmbH, Einbeck, Alemania
Taschenbuch. Condición: 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. Nº de ref. del artículo: 9781461268772
Cantidad disponible: 1 disponibles
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
Paperback / softback. Condición: New. This item is printed on demand. New copy - Usually dispatched within 5-9 working days 1027. Nº de ref. del artículo: C9781461268772
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Librería: Books Puddle, New York, NY, Estados Unidos de America
Condición: New. pp. 660. Nº de ref. del artículo: 26128014485
Cantidad disponible: 4 disponibles
Librería: Majestic Books, Hounslow, Reino Unido
Condición: New. Print on Demand pp. 660 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam. Nº de ref. del artículo: 131524426
Cantidad disponible: 4 disponibles