摘要
在不一致决策表中,以知识的包含度为基础,将一致和不一致对象分开,定义了一种新的属性重要性;为克服区分矩阵法时间复杂度随系统大小增加而指数增长的缺陷,给出分布约简的数学判定定理,提出了一种求分布约简的启发式方法。实例验证分析表明,新的属性重要性是一种更有效的启发式信息,该方法时间复杂度较低,有助于搜索最小或次优约简。
In this paper,the deficiencies of recent knowledge reduction are analyzed deeply.On the basis of the inclusion degree with separating consistent objects form inconsistent objects,a new significance of attribute is defined in inconsistent decision table.To overcome the disadvantage of ordered reduction which is based on the discernibility matrix as the time complexity is increscent exponential along with the size of decision tables,the judgment theorem with respect to distribution reduction is obtained,and a heuristic algorithm is proposed.Theoretical analyses show that the proposed heuristic information is better and more efficient than the others,and experimental results prove the validity of the heuristic algorithm in searching the minimal or optimal reduction.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第24期166-168,211,共4页
Computer Engineering and Applications
基金
河南省自然科学基金(the Natural Science Foundation of Henan Province of China under Grant No.0511011500)
河南省高校新世纪优秀人才支持计划基金(No.2006HANCET-19)
关键词
粗糙集理论不一致决策表知识约简包含度
rough set
inconsistent decision table
reduction of knowledge
inclusion degree
