Luc Devroye, Laszlo Györfi, Gabor Lugosi

Broschiertes Buch

A Probabilistic Theory of Pattern Recognition

Beschreibung

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.

Autor

Pattern recognition presents a significant challege for scientists and engineers, and many different approaches have been proposed. This book provides a self-contained account of probabilistic techniques that have been applied to the subject. Researchers and graduate students will benefit from this wide-ranging account of the field.

Produktdetails

• Stochastic Modelling and Applied Probability 31
• Verlag: Springer / Springer New York / Springer, Berlin
• Artikelnr. des Verlages: 978-1-4612-6877-2
• Softcover reprint of the original 1st ed. 1996
• Seitenzahl: 660
• Erscheinungstermin: 22. November 2013
• Englisch
• Abmessung: 235mm x 155mm x 36mm
• Gewicht: 997g
• ISBN-13: 9781461268772
• ISBN-10: 146126877X
• Artikelnr.: 40766861