Statistical Learning Theory

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Series: Adaptive and learning systems for signal processing, communications, and control

ISBN: 0471030031, 9780471030034, 9780585357058

Size: 5 MB (5643361 bytes)

Pages: 740/740

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Vladimir N. Vapnik0471030031, 9780471030034, 9780585357058

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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