Open Access
Issue
MATEC Web Conf.
Volume 139, 2017
2017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering (ICMITE 2017)
Article Number 00222
Number of page(s) 6
DOI https://doi.org/10.1051/matecconf/201713900222
Published online 05 December 2017
  1. Robert E. Schapire. The strength of weak learnability. Machine Learning, 5(2):197–227, 1990 [Google Scholar]
  2. Freund Y., Schapire R. E. A., Decision-Theoretic Generalization of OnLine Learning and an Application to Boosting. Journal of Computer and System Sciences, 1997, 55(1):119–139. [Google Scholar]
  3. Yoav Freund and Robert E. Schapire. A decision-theoretic generalization of online learning and an application to boosting. Journal of Computer and System Science, 55(1):119–139, August 1997 [Google Scholar]
  4. Thomas G. Dietterich and Ghulum Bakiri. Solving multiclass learning problems via error-correcting output codes. Journal of Artificial Intelligence Research, 2:263–286, January 1995 [Google Scholar]
  5. Robert E. Schapire and Yoram Singer. Using output codes to boost multiclass learning problems. In Machine Learning: Proceedings of the Fourteenth International Conference, pp. 313–321. 1997 [Google Scholar]
  6. Robert E. Schapire and Yoram Singer. Improved boosting algorithms using confidence-related predictions. In Proceedings of the eleventh Annual Conference on Computational Learning Theory, pp. 80–91, 1998 [CrossRef] [Google Scholar]
  7. Diao Li-li, Hu ke–yun, Lu Yu-chang, Improved Stumps Combined by boosting for Text Categorization. Journal of Software. 2202, 13(8). [Google Scholar]
  8. Yoav Freund An adaptive version of the boost by majority algorithm. In Proceedings of the Twelfth Annual Conference on Computational Learning Theory, 1999 [Google Scholar]

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