摘要
在分析基于信息系统的粗糙集理论的基础上,详细地描述了一种基于核的约减算法,接着从降低约减算法计算复杂度角度出发,提出度量单个条件属性对系统概念贡献程度的关联度的概念,修改了属性约减算法,并简要计算算法修改前后计算复杂度,实验结果表明,修改后的算法在降低时间复杂度的同时能求出次优属性集约简.
As a useful tool for Data Mining, the Rough Set Theory is widely used in the description of the correlation between attributes of relational database, the reduction of the attribute set, the counting of an attribute importance compared to other attribute importance, the discovery of rules, and so on. First, on the basis of analyzing the Rough Set Theory based on relational database, a more detailed description of attribute set reduction algorithm based on the core is given. Next, in order to reduce the computational complexity of the algorithm, the relationship conception, which describes the contribution of one of condition attributes to decision attribute, is put forward. It is applied to the algorithm above and the speed of the improved algorithm is raised. A brief comparison of the computation complexity of the old algorithm with the improved one is made. Finally, we test the improved algorithm with practical data. The result shows that the improved algorithm can not only reduce the computational complexity, but also gain the solution inferior to the best attribute reduction in most cases.
出处
《西安电子科技大学学报》
EI
CAS
CSCD
北大核心
2004年第3期431-435,共5页
Journal of Xidian University
基金
陕西省自然科学基金资助项目(2002F26)
关键词
粗集理论
近似空间
约减算法
关联度
rough set theory
approximation space
reduction algorithm
relationship
