优势关系下基于浓缩布尔矩阵的属性约简方法

在优势关系粗糙集方法(DRSA)的框架下,针对不协调的目标信息系统求属性约简。基于优势矩阵的方法是最常用的一类约简方法,但矩阵中不是所有的元素都有效。浓缩优势矩阵只保留对求约简有用的最小属性集,因而可以明显降低约简过程中的计算量。进一步地,浓缩布尔矩阵通过布尔代数的形式有效地弥补了优势矩阵生成效率低的缺点。文中将等价关系上的浓缩布尔矩阵属性约简方法扩展到优势关系上,针对优势矩阵提出了浓缩布尔矩阵的概念,建立了相应的高效约简方法,使效率得到明显提高。最后采用9组UCI数据进行实验,结果验证了所提方法的有效性。

Attribute Reduction Based on Concentration Boolean Matrix under Dominance Relations

Under the framework of dominance relation-based rough set approach (DRSA),attribute reduction was stu-died for inconsistent target information systems.The methods based on dominance matrix are the most commonly used ones,but not all elements in the matrix are valid.The concentration dominance matrix only preserves the smallest set of attributes which are useful for attribute reduction,and thus the computational complexity can be significantly reduced.On the other side,the concentration Boolean matrix further improves the generation efficiency of the dominance matrix by Boolean algebra.This paper extended the concentration Boolean matrix method under equivalence relations to that under dominance relations.The concept of concentration Boolean matrix was proposed for the dominance matrix,and the corresponding efficient reduction method was established to improve the efficiency of the reduction algorithm.Finally,nine UCI data sets were used in the experiments,and the results show the feasibility and effectiveness of the proposed method.