摘要
通过引入信息熵和条件信息熵,对信息系统中属性的必要性进行了定义,提出了一种基于条件信息熵的属性约简启发式算法。通过引入相对正域,有效地解决了不一致系统属性约简过程中产生的冗余属性问题,并分析了该算法的时间复杂度。最后,通过实例说明该算法能得到不完备决策表的最小相对约简。
This paper,by introducing information entropy and conditional information entropy,gives a definition to the necessity of attributes in incomplete decision-making table ,and puts forward a heuristic algorithm based on conditional information entropy for reduction of attribution.By introducing relatively positive region,it has solved effectively the problem of redundant attribution created in the course of reduction of attribution in inconsistencies system and has analyzed the complexity of this algorithm.Finally, an illustrative example analysis shows that this algorithm can find the minimal relative reduction for decision-making tables.
出处
《计算机工程与应用》
CSCD
北大核心
2007年第11期168-170,共3页
Computer Engineering and Applications
基金
国家自然科学基金(the National Natural Science Foundation of China under Grant No.10471036
No.60474070)
湖南省自然科学基金(the Natural Science Foundation of Hunan Province of China under Grant No.05JJ2002
No.04JJ3031)
湖南省科技厅科研项目基金(No.05FJ3074)。
关键词
粗糙集
不完备决策表
条件信息熵
启发式算法
属性约简
CIEARAWCC
rough set
incomplete decision-making table
conditional information entropy
heuristic algorithm
reduction of attribution
CIEARAWCC
