Abstract A binary encoding based fast multiclass support vector machine(SVM) is introduced. How to avoid the uneven class size of each SVM in the multiclassification system is discussed based on the encoding method. Then the strategy of searching the optimal division of different classes is proposed. Thus, with little loss of accuracy the system has a higher classification speed than the traditional ones. Therefore, the classifier is suitable for real time or online systems. Finally, the introduced classification system is evaluated by experiments.
[1] 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
2007, Vol. 20 
