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MULTI SUPPORT VECTOR MACHINES DECISION MODEL AND ITS APPLICATION
作者姓名:阎威武  陈治纲  邵惠鹤
作者单位:Dept. of Automation,Shanghai Jiaotong Univ.,Shanghai 200030,China
基金项目:Special Funds for Major State Basic Research of China (Project 973 ,G19980 3 0 415 )
摘    要:IntroductionStatistical Learning Theory( SLT) is a small-sample statistical theory by Vapnik etal.SupportVector Machine( SVM) is a novel powerful ma-chine learning method developed from SLT.SVMis powerful for the problems will small sample,nonlinearity,high dimension and local minima.Currently,SVM has many applications in the pat-tern recognition,function estimation,signal pro-cession,control,and others field1~ 3 ] .SVM en-hances generalization by principle of the structuralrisk min…


MULTI SUPPORT VECTOR MACHINES DECISION MODEL AND ITS APPLICATION
YAN Wei wu,CHEN Zhi gang,SHAO Hui he.MULTI SUPPORT VECTOR MACHINES DECISION MODEL AND ITS APPLICATION[J].Journal of Shanghai Jiaotong university,2002,7(2):220-222.
Authors:YAN Wei wu  CHEN Zhi gang  SHAO Hui he
Institution:Dept. of Automation, Shanghai Jiaotong Univ., Shanghai 200030, China
Abstract:Support Vector Machines(SVM) is a powerful machine learning method developed from statistical learning theory and is currently an active field in artificial intelligent technology. SVM is sensitive to noise vectors near hyperplane since it is determined only by few support vectors. In this paper, Multi SVM decision model(MSDM) was proposed. MSDM consists of multiple SVMs and makes decision by synthetic information based on multi SVMs. MSDM is applied to heart disease diagnoses based on UCI benchmark data set. MSDM somewhat inproves the robust of decision system.
Keywords:support vector machine  decision
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