A tutorial on  ν ‐support vector machines | Zendy

Chen PaiHsuen | Zendy; Lin ChihJen | Zendy; Schölkopf Bernhard | Zendy

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A tutorial on ν ‐support vector machines

Author(s) -

Chen PaiHsuen,

Lin ChihJen,

Schölkopf Bernhard

Publication year - 2005

Publication title -

applied stochastic models in business and industry

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.413

H-Index - 40

eISSN - 1526-4025

pISSN - 1524-1904

DOI - 10.1002/asmb.537

Subject(s) - support vector machine , statistical learning theory , computer science , kernel (algebra) , artificial intelligence , statistical learning , feature (linguistics) , kernel method , feature vector , machine learning , theoretical computer science , mathematics , discrete mathematics , philosophy , linguistics

We briefly describe the main ideas of statistical learning theory, support vector machines (SVMs), and kernel feature spaces. We place particular emphasis on a description of the so‐called ν ‐SVM, including details of the algorithm and its implementation, theoretical results, and practical applications. Copyright © 2005 John Wiley & Sons, Ltd.

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