Articoli correlati a A Probabilistic Theory of Pattern Recognition: 31

9781461268772: A Probabilistic Theory of Pattern Recognition: 31
Brossura
ISBN 10: 146126877X ISBN 13: 9781461268772
Casa editrice: Springer, 2013

Sinossi

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.

Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

Dalla quarta di copertina

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.

Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.

Editore
Springer
Data di pubblicazione
2013
Lingua
Inglese
ISBN 10 
146126877X
ISBN 13 
9781461268772
Rilegatura
Copertina flessibile
Numero di pagine
638
Contatto del produttore
non disponibile
Persona responsabile
non disponibile