Open Access
MATEC Web of Conferences
Volume 56, 2016
2016 8th International Conference on Computer and Automation Engineering (ICCAE 2016)
Article Number 01005
Number of page(s) 5
Section Computer and Information technologies
Published online 26 April 2016
  1. C. Cortes, V. Vapnik, M. L., Support vector networks 20, 273–297 (1995) [Google Scholar]
  2. W. Qingzhu, Z. Wenchao, W. Bin, Journal of Medical. Systems 39, 171 (2015) [CrossRef] [Google Scholar]
  3. Z. Ruijie, L. Bicheng, W. Fushan, Chinese. Jounal of Electronics 42, 646–652 (2014) [Google Scholar]
  4. G. Farong, W. Jiajia, X. Xu-gang, et al., Jounal of Electronics & Information.Technology 37, 1154–1159 (2015) [Google Scholar]
  5. D. K. Renuka, and P. Visalakshi, Journal of Scientific & Industrial. Research 73, 437–442 (2014) [Google Scholar]
  6. K. R. Jayadeva, S. Chandra, Pattern. Analysis & Machine. Intelligence IEEE Transactions on 29, 905–910 (2007) [Google Scholar]
  7. K. M. Arun, M. Gopal, Expert. Systems with Applications 36, 7535–7543 (2009) [Google Scholar]
  8. L. Bottou, C. Cortes, J. S. Denker, et al., InterNational Conferenceon Pattern. Recognition, IEEE Computer. Society Press, 77–82(1994) [Google Scholar]
  9. H. G. Kreßel, Advances in Kernel. Methods, 255–268 (1999) [Google Scholar]
  10. C. Angulo, X. Parra, A. Catala, Neurocomputing, KSVCR: a support vector machine for multi-class classification 55, 57–77 (2003) [Google Scholar]
  11. X. Yitian, G. Rui and W. Laisheng, Cognitive computation 5, 580–588 (2013) [Google Scholar]
  12. J. A. Nasiri, N. M. Charkari and S. Jalili, Pattern Recognition 48, 984–992 (2015) [CrossRef] [Google Scholar]
  13. C. P. Diehl, and G. Cauwenberghs, InterNational Joint Conference on Neural Networks, 2685–2690 (2003) [Google Scholar]
  14. Z. Guanhua, and H. Min, 16th InterNational Conference on Management Science and Engineering, 95–100 (2009) [Google Scholar]
  15. F. Orabona, C. Castellini, B. Caputo, et al., Pattern Recognition On-line independent support vector machines 43, 1402–1412 (2010) [Google Scholar]
  16. L. Yang, L. Kai, et al., ICACI, 18–20 (2012) [Google Scholar]

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