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Taschenbuch. Zustand: 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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In den WarenkorbPaperback. Zustand: Brand New. reprint edition. 653 pages. 9.25x6.10x1.42 inches. In Stock.
Sprache: Englisch
Verlag: Springer New York, Springer New York Nov 2013, 2013
ISBN 10: 146126877X ISBN 13: 9781461268772
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Taschenbuch. Zustand: 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.
Sprache: Englisch
Verlag: Springer New York, Springer New York, 2013
ISBN 10: 146126877X ISBN 13: 9781461268772
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: 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.
Sprache: Englisch
Verlag: Springer New York, Springer New York Apr 1996, 1996
ISBN 10: 0387946187 ISBN 13: 9780387946184
Anbieter: buchversandmimpf2000, Emtmannsberg, BAYE, Deutschland
Buch. Zustand: 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.
Sprache: Englisch
Verlag: Springer New York, Springer New York, 1996
ISBN 10: 0387946187 ISBN 13: 9780387946184
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: 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.