计算机工程与应用2018，Vol.54Issue(2)：76-81,6.DOI:10.3778/j.issn.1002-8331.1707-0379
基于加权浓缩树的粗糙集属性约简算法
摘要
Abstract
Focused on the issue that there are redundant elements in the algorithm based on the discernibility matrix, which leads to the high cost of space storage,an attribute reduction algorithm based on weighted condensed tree is pro-posed in this paper.The algorithm can further eliminate the redundant elements,compress the information in the discern-ibility matrix,and consider the effect of attribute importance in the process of constructing the tree structure.The experi-mental results are compared with the C-Tree and the discernibility information tree algorithm.The proposed algorithm can obtain better attribute reduction results,which can effectively reduce the space complexity.关键词
粗糙集/属性约简/分辨矩阵/加权浓缩树/空间复杂度Key words
rough set/attribute reduction/discernibility matrix/weighted condensed tree/space complexity分类
信息技术与安全科学引用本文复制引用
唐坤剑,容强..基于加权浓缩树的粗糙集属性约简算法[J].计算机工程与应用,2018,54(2):76-81,6.基金项目
2015年河南省科技厅"2015年度河南省高等学校重点科研项目"(No.15B520006). （No.15B520006）
