A probabilistic theory of pattern recognition:

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 me...

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Hauptverfasser: Devroye, Luc (VerfasserIn), Györfi, László (VerfasserIn), Lugosi, Gábor 1964- (VerfasserIn)
Format: Buch
Sprache:English
Veröffentlicht: New York [u.a.] Springer 1996
Schriftenreihe:Applications of mathematics 31
Schlagworte:
Zusammenfassung: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, tree 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
Beschreibung:XV, 636 S. Diagramme
ISBN:0387946187
9780387946184

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