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《Journal of Dalian University of Technology》 2008-03
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A model for simplification SVM based on guard vectors

WANG Yu,MAO Yu-xin(School of Management,Dalian University of Technology,Dalian 116024,China)  
A simplification SVM model based on guard vectors is proposed for overcoming the slow speed of training and classification for large scale training set.In order to simplify SVM,the methods of dual transform and linear programming are used to distill guard vectors;based on that,the linearly dependent support vectors are eliminated from SV set.The experiments on the UCI database are done with this algorithm.Results show that in the condition of undeclined correct rate,the running time of this model is reduced and better performance than the standard SVM is achieved.
【Fund】: 国家自然科学基金资助项目(重点项目70431001)
【CateGory Index】: TP181
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