UID:
almahu_9947362857702882
Umfang:
XV, 638 p.
,
online resource.
ISBN:
9781461207115
Serie:
Stochastic Modelling and Applied Probability, 31
Inhalt:
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.
In:
Springer eBooks
Weitere Ausg.:
Printed edition: ISBN 9781461268772
Sprache:
Englisch
Fachgebiete:
Informatik
,
Mathematik
Schlagwort(e):
Aufgabensammlung
DOI:
10.1007/978-1-4612-0711-5
URL:
http://dx.doi.org/10.1007/978-1-4612-0711-5
Bookmarklink
