Model Selection for Support Vector Machines

Chapelle, O; Vapnik, V

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Model Selection for Support Vector Machines

Chapelle, O., & Vapnik, V. (2000). Model Selection for Support Vector Machines. In S. Solla, T. Leen, & K. Müller (Eds.), Advances in Neural Information Processing Systems 12 (pp. 230-236). Cambridge, MA, USA: MIT Press.

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Item Permalink: https://hdl.handle.net/11858/00-001M-0000-0013-E4C6-7 Version Permalink: https://hdl.handle.net/21.11116/0000-0005-B5B0-7

Genre: Conference Paper

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http://papers.nips.cc/paper/1663-model-selection-for-support-vector-machines.pdf (Publisher version) Open Access status unknown

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Creators:
Chapelle, O, Author
Vapnik, V¹, Author

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1External Organizations, ou_persistent22

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Abstract: New functionals for parameter (model) selection of Support Vector Machines are introduced based on the concepts of the span of support vectors and rescaling of the feature space. It is shown that using these functionals, one can both predict the best choice of parameters of the model and the relative quality of performance for any value of parameter.

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Dates: Date issued: 2000-06

Publication Status: Issued

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Identifiers: BibTex Citekey: 2161

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Title: Thirteenth Annual Neural Information Processing Systems Conference (NIPS 1999)

Place of Event: Denver, CO, USA

Start-/End Date: 2000-11-29 - 2000-12-04

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Title: Advances in Neural Information Processing Systems 12

Source Genre: Proceedings

Creator(s):
Solla, SA, Editor
Leen, TK, Editor
Müller, K, Editor

Affiliations:
-

Publ. Info: Cambridge, MA, USA : MIT Press

Pages: - Volume / Issue: - Sequence Number: - Start / End Page: 230 - 236 Identifier: ISBN: 0-262-19450-3