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A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability, 31, Band 31) - Hardcover

Buch 1 von 30: Stochastic Modelling and Applied Probability

Devroye, Luc; Györfi, Laszlo; Lugosi, Gabor

 
9780387946184: A Probabilistic Theory of Pattern Recognition (Stochastic Modelling and Applied Probability, 31, Band 31)
Hardcover
ISBN 10: 0387946187 ISBN 13: 9780387946184
Verlag: Springer, 1996

Inhaltsangabe

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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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.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Springer
Erscheinungsdatum
1996
Sprache
Englisch
ISBN 10 
0387946187
ISBN 13 
9780387946184
Einband
Gebundene Ausgabe
Anzahl der Seiten
653
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