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Statistical Learning Theory
by Vladimir N. Vapnik


Overview - 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.  Read more...

 
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More About Statistical Learning Theory by Vladimir N. Vapnik
 
 
 
Overview
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.

 
Details
  • ISBN-13: 9780471030034
  • ISBN-10: 0471030031
  • Publisher: Wiley-Interscience
  • Publish Date: September 1998
  • Page Count: 768
  • Dimensions: 9.6 x 6.3 x 1.6 inches
  • Shipping Weight: 2.55 pounds

Series: Adaptive and Learning Systems for Signal Processing

Related Categories

Books > Mathematics > Probability & Statistics - General

 
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