Vladimir N. Vapnik, "Statistical Learning Theory"
John Wiley & Sons | ISBN : 0471030031 | Year - 1998 | DjVu | 5.8 MB | 732 Pages
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.