An Approach for Attribute Reduction and Rule Generation Based on Rough Set Theory
一种基于Rough Set理论的属性约简及规则提取方法

In this paper, the authors discuss two important issues in rough set research which are attribute reduction and value reduction. A new attribute reduction approach which can reach the best attribute reduction is presented based on discernibility matrix and logic computation. And a multivariate decision tree can be got with this method. Some improvements for a widely used value reduction method are also achieved in this paper. The complexity of acquired rule knowledge can be reduced effectively in this way.