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A short Introduction to Support Vector Machines and Kernelbased Learning

✍ Scribed by Suykens J.

Year
2003
Tongue
English
Leaves
21
Category
Library
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✦ Synopsis

β€’ Disadvantages of classical neural netsβ€’ SVM properties and standard SVM classifierβ€’ Related kernelbased learning methodsβ€’ Use of the "kernel trick" (Mercer Theorem)β€’ LS-SVMs: extending the SVM frameworkβ€’ Towards a next generation of universally applicable models?β€’ The problem of learning and generalization

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