Statistical Learning Theory (Hardcover)

A comprehensive look at learning and generalization theory. The statistical theory of learning and generalization concerns the problem of choosing desired functions on the basis of empirical data. Highly applicable to a variety of computer science and robotics fields, this book offers lucid coverage of the theory as a whole. Presenting a method for determining the necessary and sufficient conditions for consistency of learning process, the author covers function estimates from small data pools, applying these estimations to real-life problems, and much more.

General

Imprint:	John Wiley & Sons
Country of origin:	United States
Release date:	October 1998
First published:	1998
Authors:	V.N. Vapnik
Dimensions:	234 x 156 x 42mm (L x W x T)
Format:	Hardcover
Pages:	768
ISBN-13:	978-0-471-03003-4
Categories:	Books > Science & Mathematics > Mathematics > Calculus & mathematical analysis > Functional analysis Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN:	0-471-03003-1
Barcode:	9780471030034

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