A Probabilistic Theory of Pattern Recognition
Luc Devroye, László Györfi, Gábor Lugosi (auth.)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.
Kategori:
Tahun:
1996
Edisi:
1
Penerbit:
Springer-Verlag New York
Bahasa:
english
Halaman:
638
ISBN 10:
0387946187
ISBN 13:
9780387946184
Nama siri:
Stochastic Modelling and Applied Probability 31
Fail:
PDF, 10.78 MB
IPFS:
,
english, 1996
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