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《Journal of Dalian University of Technology》 2005-02
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ν-Support vector machine classifier based on linear programming

SONGJie~(1,2),TANGHuan-wen~(*1)( 1.Dept. of Appl. Math., Dalian Univ. of Technol., Dalian 116024, China;2.Dept. of Math., Shaoguan Univ., Shaoguan 512005, China )  
The ν-support vector machine (ν-SVM) classifier proposed by (Sch(o··)lkopf) has the advantage of controlling numbers of support vectors and errors compared to regular SVM. However, its formulation is more complicated which confines its applications. A new and more simple ν-SVM classifier based on linear programming is presented. The parameter also has implicit sense of controlling numbers of support vectors and errors. Furthermore the authors can use effective linear programming solvers available. Numerical tests show that the ν-SVM based on linear programming is much faster than original ν-SVM and performs as accurately as the original one.
【Fund】: 国家自然科学基金资助项目(重点项目:90103033).
【CateGory Index】: TP181
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【Co-references】
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1 SHANG Lei1,LIU Feng-jin2 (1. No. 17 Brigade of Graduate,Air Defense Forces Command Academy,Zhengzhou 450052,China;2. Command headquarter,Air Defense Artillery Brigade of Xinjiang Provincial Military Region,Urumchi 830017,China);Handwritten Number Recognition Based on Support Vector Machine[J];Ordnance Industry Automation;2007-03
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