Statistical Learning Theory

By: Vladimir N. Vapnik

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Hardcover | 16 September 1998 | Edition Number 1

At a Glance

Hardcover
768 Pages

Dimensions(cm)
24.13 x 16.26 x 3.56

Hardcover

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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.

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