摘要
属性约简是粗糙集理论的一个重要内容,是进行知识获取中的核心问题之一.本文在粗糙集理论的基础上构造了区分图,在区分图上以属性的重要度作为启发信息,快速缩小搜索空间,求解最小属性约简.给出了一个最坏情况下时间复杂度为max（O（｜C｜^2）,O（｜C‖U｜^2））的快速属性约简算法.该算法统一考虑一致性决策表和不一致性决策表两种情况下的属性约简.
Attribute reduction is one of the important contents of rough set and the key problems for the knowledge acquisition.Based on the rough set theory,the different graph is constructed,and on the basis of the different graph,the attribution importance is acted as heuristic function to reduce search space quickly and find a minimal attribute reduction.A quickly attribution reduction algorithm is provided and the bad time complexity is max（O（｜C｜^2）,O（｜C｜｜U｜^2））.The consistent decision table and the inconsistent decision table are considered in this algorithm.
出处
《山东师范大学学报（自然科学版）》
CAS
2007年第4期17-20,共4页
Journal of Shandong Normal University(Natural Science)
关键词
粗糙集
属性约简
区分图
算法复杂度
rough set
attribute reduction
different graph
algorithm complexity
