一种新的不完备信息系统属性约简算法

A new attribute reduction algorithm in an incomplete information system

针对不完备信息系统提出一种基于粗糙集理论的属性相对约简方法。利用粗糙集等价关系的扩展,即容差关系为基础提出容差关系相似矩阵的概念,通过引入广义决策函数的限制来解决不完备信息系统约简的不一致性问题,通过容差关系相似矩阵求不完备信息系统的核属性,利用属性在容差关系相似矩阵中出现的频率给出了属性重要度的计算公式,利用属性重要度为约简的启发式规则,并运用折半启发式算法减少扩展次数,提高约简速度。实验表明该方法简单、有效。

Against the incomplete information system, this paper proposed a method of attribute relative reduction based on rough set theory. This reduction method gave the concept of tolerance relationship similar matrix via using an extension of e- quivalence relationship of rough set theory, which was called tolerance relationship. It solved the problem of inconsistency in the incomplete information system through the introduction of restrictions of the generalized decision function. It calculat- ed the core attributes of incomplete information systems via the tolerance relationship similar matrix. It applied attribute sig- nificance, which this paper put forward based on attribute frequency in the tolerance relationship similar matrix, as the heu- ristic konwledge. It made use of binsearch heuristic algorithm to calculate the candidate attribute expansion so that it can reduce the expansion times to speed up reduction. Experiment results show that this method is simple and effective.