佛山科学技术学院学报（自然科学版）2024，Vol.42Issue(3)：14-19,6.
基于正域向量的决策粗糙集属性约简
Attribute reduction in decision-theoretic rough set models based on positive region vector
摘要
Abstract
In the decision-theoretic rough set model,the existing positive region at the level of classification is integrated by union.However,the attribute reduction based on this method is not consistent with that based on discernibility matrix.This paper analyzes the reason in depth and proposes an attribute reduction based on positive region vector.It is proved that the positive region vector preservation is consistent with the results obtained by discernibility matrix method.Finally,an example is given to illustrate their consistency.关键词
决策粗糙集模型/正域向量/属性约简/差别矩阵Key words
decision-theoretic rough set models/positive region vector/attribute reduction/discernibility matrix分类
信息技术与安全科学引用本文复制引用
黄国顺..基于正域向量的决策粗糙集属性约简[J].佛山科学技术学院学报（自然科学版）,2024,42(3):14-19,6.基金项目
广东省基础与应用基础研究基金项目(2021B1515120048) （2021B1515120048）
