简介:TheChineseOpticsandAppliedOpticsAbstracts,sponsoredbytheDocumentationandIn-formationCenteroftheChineseAcademyofSciences,theOpticalInformationNetworkoftheChineseAcademyofSciencesandtheChangehunInstituteofOptics,FineMechanicsandPhysicsoftheChineseAcademyofSciences,isoneoftheseriesofscienceandtechnologyin-dexingperiodicalspublishedbytheChineseAcademyofSciences.
简介:摘要本文在将数值型数据标准化的基础上,将分类数据细分为二元数据和类型数据,并用相异度系数距离计算分类数据之间的距离,并且赋予二元和类型数据相应的权重,来改进k-prototypes聚类算法,使该算法满足不同要求的混合属性数据聚类,最后通过C#语言,在ArcEngine2010版本上实现。