Principles of nonparametric learning /

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 esti...

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Bibliographic Details

Corporate Author:	SpringerLink (Online service)
Other Authors:	Györfi, László
Format:	eBook
Language:	English
Published:	Wien ; New York : Springer, [2002]
Series:	Courses and lectures ; no. 434.
Subjects:	Nonparametric statistics. Computational learning theory. Electronic books.
Online Access:	Connect to the full text of this electronic book