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《Journal of Shanxi University(Natural Science Edition)》 2009-04
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Granular Support Vector Machine Learning Model

WANG Wen-jian1,2,GUO Hu-sheng1(1.School of Computer and Information Technology,Shanxi University,Taiyuan 030006,China;2.Key Laboratory of Computational Intelligence and Chinese Information Processing of Ministry of Education,Taiyuan 030006,China)  
Granular Support Vector Machine(GSVM) is a novel machine learning model based on granular computing theory and statistical learning theory.It can solve the low efficiency learning problem that existing in traditional Support Vector Machine(SVM),and obtain the satisfactory generalization performance as well.This paper analyzes the GSVM models based on original space and proposes an GSVM model based on kernel space(KGSVM).The experiments on benchmark datasets demonstrate the effectiveness of the proposed approach.
【Fund】: 国家自然科学基金(60673095);; 国家863计划项目(2007AA01Z165);; 教育部科学技术研究重点资助项目(208021);; 教育部新世纪优秀人才支持计划资助项目(NCET-07-0525);; 山西省青年学术带头人支持计划资助项目;; 山西省留学归国人员项目(2008-14);; 山西省自然科学基金重点项目(2009011017-2)
【CateGory Index】: TP18
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【Citations】
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【Co-citations】
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