混合值不完备系统的双邻域粗糙集分类方法

针对混合值不完备系统,提出一种基于双邻域粗糙集模型的分类方法.首先,定义一个新的不确定距离度量函数-----联系度距离函数,进而建立基于联系度距离函数的双邻域粗糙集模型;然后,基于所建立的模型讨论该模型的属性约简算法,并给出基于属性约简、覆盖约简的双邻域粗糙集规则学习分类算法;最后,通过多个UCI 数据集进行实证分析,结果表明所提出的分类算法是客观有效的,特别是在缺失值较多的情况下,其优势更加明显.

Double-neighborhood rough set classification method in incomplete decision system with hybrid value

In order to process the incomplete decision system with hybrid value, a classification method based on the double-neighborhood rough set model is proposed in this paper. Firstly, an uncertain distance function --- Connection degree distance function is defined, and the double-neighborhood rough set model based on connection degree distance function is constructed. Then, based on the constructed model, an attribute reduction algorithm is discussed, and a classification algorithm based on attribute reduction and covering reduction is provided. Finally, some experiments are carried out on UCI data sets. The experiments results show that the proposed classification algorithm is objective and effective, and it is more effective when the missing value is abounded.