关键词: 粗糙集, 核, 属性约简, 正域

Abstract: Core is an essential component of attribute reduction. Though analyzing the significancy of every attribute in core, it is found that the significanfy of every attribute is different. The attributes with less siginicancy can affect the accuracy of classifier. Therefore, in this paper, Quasi-core is proposed by deleting the attributes with less significancy than most of attributes in core, and a new heuristic attribute reduction algorithm is designed based on the Quasi-core. Experimental result shows that the reduct with less attributes are obtained by the algorithm, and classifier constructed based the reduct has higher classifier accuracy.

Key words: rough set, core, attribute reduction, positive region