面向属性归纳下的多层次决策规则获取算法

针对信息系统中容错能力差、样本量小以及条件相同而决策结果不一致等问题,提出了一种在面向属性归纳下基于变精度粗糙集模型的多层次决策规则获取算法.首先,在条件属性的概念层次下分析高低层次决策表在变精度模型中下近似、正域、边界域和负域间关系.基于各层次决策表关系图,先由最高层决策表自顶向下按经典粗糙集模型获取确定性规则,然后再由最底层决策表自底向上获取更抽象的规则.实例分析说明了该算法的可行性.

An Algorithm of Extracting Multi-hierarchical Decision Rules in Attribute-Oriented Induction

For the problems of poor fault-tolerant ability,small sample size and inconsistent decision results under equal conditions in information systems,an algorithm of extracting multi-hierarchical decision rules in attribute-oriented induction is proposed based on the variable precision rough set model.In the concept hierarchies of condition attributes,the relationships of the low approximations,positive regions,boundary regions and negative regions in the variable precision model between the high level decision table and its corresponding low level one are analyzed firstly.Based on the relationship diagram of different-level decision tables,the certain decision rules are obtained from the highest-level decision table to the bottom one using the traditional rough set model.Then more abstract decision rules are acquired from bottom to top along the relationship diagram based on the lowest-level decision table.The feasibility of the algorithm is validated by a case study.