杂合数据的粗糙集属性约简方法

针对决策表中属性取值为杂合数据的情况,提出了基于粗糙集理论的属性约简算法.首先给出了对象间在杂合数据下的相似度计算定义.为了获取合理的对象集合的软划分,给出了阈值计算的最优化模型,并基于粗糙集的上、下近似的概念,得到对象集合在条件属性下的上、下近似的覆盖划分.之后,通过各对象基于条件属性和决策属性的上、下近似下的分布矩阵描述,利用最大分布矩阵,直观地得到两种不同观点下的约简结果.实验结果表明了本算法的合理和有效性.

Rough Set Based Attribute Reduction Algorithm for Hybrid Data

With regard to the attribute values in decision table,which are described with hybrid data,a new algorithm of attribute reduction based on rough set theory is proposed.First,the similarity relations among objects with hybrid data are defined.In order to obtain reasonable soft partitions among objects,the optimization model for threshold accounting is presented.Then,based on the upper and lower approximation concept from rough set theory,the covering upper and lower similar partitions among objects are obtai...