Nyström Approximate Model Selection for LSSVM-Reference-Cited by-同舟云学术

Nyström Approximate Model Selection for LSSVM

Published:2012 Issue: Volume: Page:282-293
ISSN:0302-9743
Container-title:Advances in Knowledge Discovery and Data Mining
language:
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Author:

Ding Lizhong,Liao Shizhong

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-30217-6_24.pdf

Reference19 articles.

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2. Cawley, G.C., Talbot, N.L.C.: Preventing over-fitting during model selection via Bayesian regularisation of the hyper-parameters. Journal of Machine Learning Research 8, 841–861 (2007)

3. Cawley, G.C., Talbot, N.L.C.: On over-fitting in model selection and subsequent selection bias in performance evaluation. Journal of Machine Learning Research 11, 2079–2107 (2010)

4. Chapelle, O., Vapnik, V.: Model selection for support vector machines. In: Advances in Neural Information Processing Systems, vol. 12, pp. 230–236. MIT Press, Cambridge (2000)

5. Chapelle, O., Vapnik, V., Bousquet, O., Mukherjee, S.: Choosing multiple parameters for support vector machines. Machine Learning 46(1), 131–159 (2002)

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