混合值不完备系统的双邻域粗糙集分类方法  

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

作　　者：黄恒秋 曾玲[2] 黎利辉 HUANG Heng-qiu;ZENG Ling;LI Li-hui(School of Mathematics and Computer Science, Guangxi Normal University for Nationalities, Chongzuo 532200, China;School of Mathematics and Computing Science, Guilin University of Electronic Technology, Guilin 541004, China)

机构地区：[1]广西民族师范学院数学与计算机科学学院,广西崇左532200 [2]桂林电子科技大学数学与计算科学学院,广西桂林541004

出　　处：《控制与决策》2018年第7期1207-1214,共8页Control and Decision

基　　金：广西重点培育学科(应用数学)建设项目(SXYB2014005;SXYB2016001);国家民委科研项目(14GSZ015)

摘　　要：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.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.

关 键 词：混合值不完备系统 双邻域粗糙集 联系度距离 分类 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]