Details

Autor(en) / Beteiligte

• Devroye, Luc
• Györfi, Laszlo
• Lugosi, Gabor

Titel

A Probabilistic Theory of Pattern Recognition

Auflage

1

Ort / Verlag

New York, NY: Springer

Erscheinungsjahr

1996

Link zum Volltext

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• 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.