Principles of Nonparametric Learning

Paperback Engels 2002 2002e druk 9783211836880
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Samenvatting

The book provides systematic in-depth analysis of nonparametric learning. It covers the theoretical limits and the asymptotical optimal algorithms and estimates, such as pattern recognition, nonparametric regression estimation, universal prediction, vector quantization, distribution and density estimation and genetic programming.
The book is mainly addressed to postgraduates in engineering, mathematics, computer science, and researchers in universities and research institutions.

Specificaties

ISBN13:9783211836880
Taal:Engels
Bindwijze:paperback
Aantal pagina's:335
Uitgever:Springer Vienna
Druk:2002

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Inhoudsopgave

Pattern classification and learning theory (G. Lugosi).- Nonparametric regression estimation (L. Györfi, M. Kohler).- Universal prediction (N. Cesa-Bianchi).- Learning-theoretic methods in vector quantization (T. Linder).- Distribution and density estimation (L. Devroye, L. Györfi).- Programming applied to model identification (M. Sebag)

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€ 172,07
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        Principles of Nonparametric Learning