南京理工大学学报（自然科学版）2016，Vol.40Issue(4)：444-449,6.DOI:10.14177/j.cnki.32-1397n.2016.40.04.011
决策粗糙集属性约简：一种局部视角方法
Local attribute reduction approach based on decision-theoretic rough set
摘要
Abstract
Compared with classical rough sets,the decision-theoretic rough set model takes cost into account,which brings new challenges for solving attribute reduction in rough set. Some attribute reduction methods of decision-theoretic rough set have been put forward. However,the standards of these methods are based on all decision classes. It is too stringent for some condition. To solve this problem,from a local perspective,the idea Local attribute reduction is proposed. The experimental results based on the heuristic algorithm show that compared with the reduction based on all decision classes,Local attribute reduction can generate more positive domain rules and reduce the number of attributes.关键词
属性约简/代价/启发式算法/Local约简/单调性准则/正域规则/决策粗糙集Key words
attribute reduction/cost/heuristic algorithm/Local attribute reduction/monotonic criterion/positive domain rule/decision-theoretic rough set分类
信息技术与安全科学引用本文复制引用
王宇,杨志荣,杨习贝..决策粗糙集属性约简：一种局部视角方法[J].南京理工大学学报（自然科学版）,2016,40(4):444-449,6.基金项目
国家自然科学基金(61572242,61272419,61305058,61373062) （61572242,61272419,61305058,61373062）
江苏省青蓝工程人才项目 （）
中国博士后科学基金(2014M550293) （2014M550293）
