一种基于随机决策信息系统的属性约简算法

A ATTRIBUTE REDUCTION ALGORITHM BASED ON RANDOM INFORMATION FOR DECISION SYSTEMS

研究基于随机决策信息系统的属性约简算法,发现现有文献存在着运算量大、找到的不是约简或仅找到核的缺陷,本文提出了一种属性约减递归算法。该算法能够计算所有约简和核,而且算法时间复杂度少,运算效率高。经实例验证,该算法有很强的可行性和有效性。

This paper researches attributes reduction based on random information for decision systems, and finds some flaws in the existing papers,a attributes sets reduction recursion algorithm is presented. The algorithm can calculate all attribute reductions and core, have small time complications and high operation efficiency. The experimental results show that the algorithm is verified to be more feasible and effective at last.