Learning Kernel Classifiers: Theory and Algorithms
(Part of the Adaptive Computation and Machine Learning Series)
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Book Overview
An overview of the theory and application of kernel classification methods. Linear classifiers in kernel spaces have emerged as a major topic within the field of machine learning. The kernel technique takes the linear classifier-a limited, but well-established and comprehensively studied model-and extends its applicability to a wide range of nonlinear pattern-recognition tasks such as natural language processing, machine vision, and biological sequence...
Format:Paperback
Language:English
ISBN:0262546590
ISBN13:9780262546591
Release Date:November 2022
Publisher:MIT Press
Length:384 Pages
Weight:1.34 lbs.
Dimensions:0.8" x 7.0" x 9.0"
Age Range:18 years and up
Grade Range:Postsecondary and higher
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