Support vectors selection for supervised learning using an ensemble approach

Proceedings - International Conference on Pattern Recognition

Volumn , Issue , 2010, Pages 37-40

  Guo, Li ^a   Boukir, Samia ^a   Chehata, Nesrine ^a  

^a GHYMAC Laboratory   (France)

Author keywords

Ensemble learning; Margin; SVM

Indexed keywords

ENSEMBLE CLASSIFIERS; ENSEMBLE LEARNING; LARGE DATASETS; MARGIN; PATTERN CLASSIFICATION; PROCESSING TIME; SELECTION METHODS; SPEED-UPS; SUPPORT VECTOR; SVM; TRAINING SETS;

CLASSIFICATION (OF INFORMATION); CLASSIFIERS; PATTERN RECOGNITION; VECTORS;

SUPPORT VECTOR MACHINES;

EID: 78149481675     PISSN: 10514651     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICPR.2010.18     Document Type: Conference Paper

References (8)

1. V. Vapnik, The Nature of Statistical Learning Theory. New York: Springer, 1995, no. ISBN 0-387-98780-0.
2. H. Shin and S. Cho, "Pattern selection for support vector classifiers," in The Third International Conference on Intelligent Data Engineering and Automated Learning, ser. Lecture Notes In Computer Science, vol. 2412, 2002, pp. 469-474.
3. S. Abe, Support Vector Machines for Pattern Classification, ser. Advances in Pattern Recognition, 1, Ed. Springer, 2005, iSBN-10: 1852339292.
4. L. Breiman, "Bagging predictors," Machine Learning, vol. 24, no. 2, pp. 123-140, Aug. 1996. [Online]. Available: http://dx.doi.org/10.1007/ BF00058655
5. R. E. Schapire, Y. Freund, P. Bartlett, and W. S. Lee, "Boosting the margin: a new explanation for the effectiveness of voting methods," The Annals of Statistics, vol. 26, no. 5, pp. 1651-1686, 1998.
6. J. C. Platt, Advances in Kernel Methods: Support Vector Machines. Cambridge: The MIT Press, 1999, ch. Fast Training of Support Vector Machines Using Sequential Minimal Optimization, pp. 185-208.
7. L. Breiman, J. Friedman, R. Olshen, and C. Stone, Classification and Regression Trees. Belmont: Wadsworth, 1984.
8. A. Asuncion and D. Newman, "UCI machine learning repository," 2009. [Online]. Available: http://www.ics.uci.edu/~mlearn/MLRepository.html