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《Computer Technology and Development》 2010-02
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A Kind of Novel Fast Fuzzy Support Vector Machines

SHI Qi-quan,LI Xiao-ming,XIAO Ci-yuan(Dept.of Sciences,Southwest Petroleum University,Chengdu 610500,China)  
Proposes a kind of fast fuzzy support vector machines to solve the problem of long training time and low training efficiency by improved algorithm.The definition of membership function in the new algorithm can give the smaller memberships to the data away from separating hyperplane which can not be the support vector,so it reduces the data in the training sample set.Meanwhile,it expends to multi-classes fast fuzzy support vector machines using DAG.Experimental results indicate that the algorithm reduces the training time on the premise of guaranteeing the testing accuracy.
【Fund】: 四川省教育厅重点基金项目(072A143)
【CateGory Index】: TP181
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