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广义最大间隔球形支持向量机
引用本文:文传军,柯佳.广义最大间隔球形支持向量机[J].计算机工程与应用,2012,48(29):177-180,209.
作者姓名:文传军  柯佳
作者单位:1. 常州工学院理学院,江苏常州,213002
2. 江苏大学计算机科学与通信工程学院,江苏镇江,212013
基金项目:国家自然科学基金(No.61170126);常州工学院校级课题(No.YN1010,No.YN1030)
摘    要:针对多类分类问题,提出一种超球支持向量机算法——广义最大间隔球形支持向量机,该算法利用两同心超球将正负类样本分隔开来,最大化两超球半径的差异,从而挖掘正负类样本的鉴别信息,同时对超球类支持向量机算法判决规则进行改进,引入模糊隶属度补充判决,弥补二类分类器投票决策的缺陷.理论分析了算法的相关性质,通过仿真实验验证了该算法的有效性.

关 键 词:支持向量机  支持向量数据描述  最大间隔最小体积球型支持向量机  模糊隶属度

General maximal-interval hypersphere SVM
WEN Chuanjun , KE Jia.General maximal-interval hypersphere SVM[J].Computer Engineering and Applications,2012,48(29):177-180,209.
Authors:WEN Chuanjun  KE Jia
Affiliation:1.School of Science,Changzhou Institute of Technology,Changzhou,Jiangsu 213002,China 2.School of Computer Science and Communication Engineering,Jiangsu University,Zhenjiang,Jiangsu 212013,China
Abstract:For multi-class classification,a new hypersphere SVM algorithm is given in this paper,and named as General Maximal-interval Hypersphere SVM(GMHSVM).In this algorithm,positive and negative samples are separated by two different concentric hyperspheres,the model target is to maximize the difference of two hyperspheres’radious,which represents the discriminant information of two classes,meanwhile,fuzzy membership is introduced to improve the decision rules of hypersphere SVM,which makes up the voting-decision flaw of two-class classifier.Related properties are obtained by theoretical analysis,simulation experiment results show the effectiveness of the proposed method.
Keywords:
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