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Ajouter au panierTaschenbuch. Etat : 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.
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Ajouter au panierPaperback. Etat : Brand New. reprint edition. 653 pages. 9.25x6.10x1.42 inches. In Stock.
Edité par Springer New York, Springer New York Nov 2013, 2013
ISBN 10 : 146126877X ISBN 13 : 9781461268772
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : 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.
Edité par Springer New York, Springer New York, 2013
ISBN 10 : 146126877X ISBN 13 : 9781461268772
Langue: anglais
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Ajouter au panierTaschenbuch. Etat : 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.
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Ajouter au panierEtat : As New. Unread book in perfect condition.
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Springer New York, Springer New York Apr 1996, 1996
ISBN 10 : 0387946187 ISBN 13 : 9780387946184
Langue: anglais
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Ajouter au panierBuch. Etat : 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.
Edité par Springer New York, Springer New York, 1996
ISBN 10 : 0387946187 ISBN 13 : 9780387946184
Langue: anglais
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
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Ajouter au panierBuch. Etat : 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.
Edité par Springer New York Nov 2013, 2013
ISBN 10 : 146126877X ISBN 13 : 9781461268772
Langue: anglais
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
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Ajouter au panierTaschenbuch. Etat : 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.
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Ajouter au panierEtat : 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.