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Support Vector Machines are Universally Consistent

✍ Scribed by Ingo Steinwart

Publisher: Elsevier Science
Year: 2002
Tongue: English
Weight: 220 KB
Volume: 18
Category: Article
ISSN: 0885-064X
DOI: 10.1006/jcom.2002.0642

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✦ Synopsis

We show that support vector machines of the 1-norm soft margin type are universally consistent provided that the regularization parameter is chosen in a distinct manner and the kernel belongs to a specific class}the so-called universal kernels}which has recently been considered by the author. In particular it is shown that the 1-norm soft margin classifier with Gaussian RBF kernel on a compact subset X of R d and regularization parameter c n ¼ n bÀ1 is universally consistent, if n is the training set size and 05b51=d: # 2002 Elsevier Science (USA)

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