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A Probabilistic Theory of Pattern Recognition

Produktform: Buch / Einband - flex.(Paperback)

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.weiterlesen

Dieser Artikel gehört zu den folgenden Serien

Sprache(n): Englisch

ISBN: 978-1-4612-6877-2 / 978-1461268772 / 9781461268772

Verlag: Springer US

Erscheinungsdatum: 22.11.2013

Seiten: 638

Auflage: 1

Autor(en): Luc Devroye, László Györfi, Gábor Lugosi

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