概念层次中基于粗糙集的优化可信规则获取

Optimal credible rules based on rough sets in concept hierarchies

随着系统中数据量剧增,规则太多以及不同决策者对规则有不同层次需求等问题,概念层次提供了一种解决方法。讨论条件属性具有概念层次的情况下,利用粗糙集理论分析属性在不同层次组合下的正域和规则关系,自顶向下提出了概念层次中基于粗糙集的优化可信规则获取的算法。该算法改进了现有的属性约简策略,借助描述子实现属性约简并获取优化可信规则。考虑到层次上正域为空和正域没有新增对象的特殊情况,提高了规则获取的效率。最后通过实例分析说明该算法的可行性。

The concept hierarchies provide a new way to solve such problems as the data are increasing too fast,there are so many rules,and different decision makers need obtain some rules from different hierarchies.In the context that every condition attribute had a concept hierarchy,the relations of positive regions and rules from different levels were analyzed based on rough set theory.Then,the algorithm of optimal credible rules based on rough sets in concept hierarchies was proposed,which was along with concept hierarchies from top to down.The algorithm improved the existing reduction strategy,realized the reduction and obtained the optimal credible rules by descriptors.Besides,it also considered there was null or not a new object in the positive region,and the effectiveness of extracting rules was improved.Finally,the feasibility of this algorithm was validated by an example.