Attribute Reduction With Discernibility Matrix Approaches

摘要：

With the large number of attributes, reduction of its attributes is a crucial step in the clustering analysis of data The main task of the present work is to construct a novel clustering analysis method motivated by the fundamental idea from information system, the computer simulation shows that the reduction of attributes gives a better accuracy of clustering rate.

关键词： Reduction of attribute Information system Indiscernibility matrix

作者: Lishi zhang Shengzhe Gao

作者单位: School of Science, Dalian Ocean University, Dalian 116023

会议类型: 国际会议

会议名称: The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)

会议地点: 太原

会议语种:英文

页码: 2712-2714

在线出版日期: 2012-05-23（万方平台首次上网日期，不代表论文的发表时间）