Crowds classification using hierarchical cluster, rough sets, principal component analysis and its combination

摘要：

13 kind of nationalities crowds data classification using hierarchical cluster(HC), rough sets(RS), principal component analysis(PCA) and its combination,the result shows : first,rough sets and principal component analysis can dimensionality reduction and de-noising; second, hierarchical cluster after rough sets(RSHC), principal component analysis after rough sets(PCARS), principal component analysis after principal component anatysis(PCAPCA), hierarchical cluster after principal component analysis (HCPCA),rough sets after principal component analysis(PCARS) are similarly result Then, according to different practical application select different methods or combinative methods, which can maximize their advantages and minimize their disadvantages.

关键词： hierarchical cluster (HC) rough sets (RS) principal component analysis (PCA) combination

作者: Bin Nie Jianqiang Du Hongning Liu Guoliang Xu Zhuo Wang Yan He Bingtao Li

作者单位: school of computer, jiang xi university of traditional Chinese medicine, NanChang, JiangXi,China key key laboratory of modern preparation of TCM, ministry of education, jiang Xi University of tradition Software College of Nanchang University, NanChang, JiangXi,China School of computer, jiang xi university of traditional Chinese medicine, NanChang, JiangXi,China

会议类型: 国际会议

会议名称: 2009 International Forum on Computer Science-Technology and Applications(2009年国际计算机科学技术与应用论坛 IFCSTA 2009)

会议地点: 重庆

会议语种:英文

页码: 287-290

在线出版日期: 2009-12-25（万方平台首次上网日期，不代表论文的发表时间）