Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
(Part of the Adaptive Computation and Machine Learning Series)
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Book Overview
A comprehensive introduction to Support Vector Machines and related kernel methods. In the 1990s, a new type of learning algorithm was developed, based on results from statistical learning theory: the Support Vector Machine (SVM). This gave rise to a new class of theoretically elegant learning machines that use a central concept of SVMs---kernels--for a number of learning tasks. Kernel machines provide a modular framework that can be adapted to different...
Format:Hardcover
Language:English
ISBN:0262194759
ISBN13:9780262194754
Release Date:December 2001
Publisher:MIT Press
Length:648 Pages
Weight:0.35 lbs.
Dimensions:1.4" x 8.2" x 10.2"
Age Range:18 years and up
Grade Range:Postsecondary and higher
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