区间值数据的代价敏感特征选择  

Cost⁃sensitive feature selection for interval⁃valued data

作　　者：刘琼[1,2] 代建华 陈姣龙 Liu Qiong;Dai Jianhua;Chen Jiaolong(Hunan Provincial Key Laboratory of Intelligent Computing and Language Information Processing,Hunan Normal University,Changsha,410081,China;College of Information Science and Engineering,Hunan Normal University,Changsha,410081,China)

机构地区：[1]智能计算与语言信息处理湖南省重点实验室,湖南师范大学,长沙410081 [2]湖南师范大学信息科学与工程学院,长沙410081

出　　处：《南京大学学报（自然科学版）》2021年第1期121-129,共9页Journal of Nanjing University（Natural Science）

基　　金：国家自然科学基金(61976089,61473259);湖南省科技计划(2018TP1018,2018RS3065)。

摘　　要：特征选择是区间值信息系统中数据分析的研究热点,但是目前针对区间值数据提出的特征选择很少考虑数据自身的测试代价和误分类代价.为了解决这一问题,首先利用邻域粗糙集给出了区间值邻域的概念,进而重新定义了基于区间值邻域的熵结构,其次构造了区间值系统下的代价敏感函数,最后提出基于代价敏感的区间值特征选择方法.通过实验对比,证实了该方法的合理性和有效性.Feature selection is a research hotspot of data analysis for interval⁃valued information systems.However,most existing feature selection methods for interval⁃valued data neglect the test cost and misclassification cost in the data.In order to solve this problem,the concept of interval⁃valued neighborhood is defined by neighborhood rough set theory,and the entropy construct based on interval⁃valued neighborhood is constructed.Then,the cost sensitive function for interval⁃valued information system is designed.Finally,the feature selection approach based on the cost sensitive for interval⁃valued data is proposed.Through the comparative experiments,the rationality and effectiveness of the proposed approach is verified.

关 键 词：特征选择 区间值数据 区间邻域粗糙集 代价敏感 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]