Vapnik V N. Statistical Learning Theory. New York, USA: Wiley, 1998
[2]
Deng Naiyang, Tian Yingjie. The New Method for Data Mining: Support Vector Machine. Beijing, China: Science Press, 2004 (in Chinese) (邓乃扬,田英杰.数据挖掘中的新方法——支持向量机.北京:科学出版社, 2004)
[3]
Hsu C W, Lin C J. A Comparison of Methods for MultiClass Support Vector Machines. IEEE Trans on Neural Networks, 2002, 13(2): 415425
[4]
Platt J C, Cristianini N, ShaweTaylor J. Large Margin DAG’s for Multiclass Classification // Solla S A, Leen T K, Müller K R, eds. Advances in Neural Information Processing Systems. Cambridge, USA: MIT Press, 2000, 12: 547553
[5]
Weston J, Watkins C. MultiClass Support Vector Machines. Technical Report, CSDTR9804, Royal Holloway, UK: University of London. Department of Computer Science, 1998
[6]
Rifkin R, Klautau A. In Defense of OnevsAll Classification. Journal of Machine Learning Research, 2004, 5(1): 101141
[7]
Wang Liguo, Zhang Ye, Gu Yanfeng. The Research of Simplification of Structure of MultiClass Classifier of Support Vector Machine. Journal of Image and Graphics, 2005, 10(5): 571574 (in Chinese) (王立国,张 晔,谷延锋.支持向量机多类目标分类器的结构简化研究.中国图象图形学报, 2005, 10(5): 571574)
[8]
Chew H G, Crisp D J, Bogner R E. Target Detection in Radar Imagery Using Support Vector Machines with Training Size Biasing [EB/OL]. [20010401]. http://www.eleceng.adelaide.edu.au/personal/hgchew/svm.html
[9]
Wang Ling. Intelligent Optimization Algorithms with Applications. Beijing, China: Tsinghua University Press, 2001 (in Chinese) (王 凌.智能优化算法及其应用.北京:清华大学出版社, 2001)
[10]
Xu Rui, Wunsch D. Survey of Clustering Algorithms. IEEE Trans on Neural Networks, 2005, 16(3): 645678
[11]
Michie D, Spiegelhalter D J, Taylor C C. Machine Learning, Neural and Statistical Classification [EB/OL]. [20060619]. ftp://ncc.up.pt/pub/statlog
[12]
Chang C C, Lin C J. LIBSVM: A Library for Support Vector Machines [DB/OL]. [20060619]. http://www.csie.ntu.edu.tw/~cjlin/libSVM
