计算机应用研究2017，Vol.34Issue(1)：110-113,122,5.DOI:10.3969/j.issn.1001-3695.2017.01.023
基于不完备区间值信息系统的决策粗糙集
Decision-theoretic rough set based on incomplete interval-valued information system
摘要
Abstract
In incomplete interval-valued information system,this paper proposed the decision-theoretic rough set based on maximal consistent class.Considering the insufficient about attribute similarity in incomplete interval-valued information sys-tem,it provided the improved attribute similarity.Then,in order to solve the model’s high redundancy and low classification accuracy in the information system,this paper replaced equivalence class with the maximal consistent class and set up the de-cision-theoretic rough set model combined with Bayesian smallest risk theory.And it proved that set up the model based on maximal consistent class can improve the classification accuracy.Finally,it proposed the attribute reduction algorithm based on indiscernibility matrix and remains distribution of positive region and applied it to a case.关键词
不完备区间值信息系统/属性相似度/决策粗糙集/区分矩阵Key words
incomplete interval-valued information system/attribute similarity/decision-theoretic rough set/indiscernibility matrix分类
信息技术与安全科学引用本文复制引用
张鑫,李续武,路艳丽,陈玉金..基于不完备区间值信息系统的决策粗糙集[J].计算机应用研究,2017,34(1):110-113,122,5.基金项目
国家自然科学基金资助项目 （）
