基于粗集理论的缺省规则挖掘模型

A Rough Set Model to Mine Default Rules

提出了一种基于粗集的缺省规则挖掘模型 ,以利于在信息不完备情况下进行推理和决策 .该模型从已知决策系统出发 ,建立了处于不同简化层次上的一系列子系统 ,并将其作为简约格中的节点 ,然后推导出每个节点的规则集 .在应用模型进行推理和决策分析时 ,用给定对象的信息与模型中相应节点的规则进行匹配 ,然后按照某种评判准则得出结论 .这种模型可以很方便地根据给定的信息 。

A rough set model to mine default rules was presented in order to reason and solve the decision question with incomplete information.The model created a series of subsystems from the known decision system at different reduced levels to form a reduced lattice,and then reasoned its own rule set at each node. When reasoning and analyzing,the given object information was used to match the rules of the cor- responding node and a conclusion was reached according to an evaluation criterion. It can conveniently ar- rive at a conclusion as good as possible at the matching subsystem according to the given information.