基于权重邻域熵的数值型信息系统属性约简算法

doi:10.6040/j.issn.1672-3961.0.2022.310

山东大学学报 (工学版) ›› 2024, Vol. 54 ›› Issue (1): 33-44.doi: 10.6040/j.issn.1672-3961.0.2022.310

• 机器学习与数据挖掘 • 上一篇

基于权重邻域熵的数值型信息系统属性约简算法

陈宝国¹,邓明^{1 *},陈金林²

1.淮南师范学院计算机学院, 安徽淮南 232038;2.南京航空航天大学电子信息工程学院, 江苏南京 211106

发布日期:2024-02-01
作者简介:陈宝国(1978— ),男,安徽安庆人,副教授,硕士,主要研究方向为粗糙集、粒计算、数据挖掘. E-mail:bgchen0706@163.com. *通信作者简介:邓明(1976— ),男,安徽寿县人,教授,硕士生导师,博士,主要研究方向为安全信息处理、智能数据处理. E-mail:mdeng76@163.com
基金资助:
安徽省高校自然科学研究重点项目(KJ2018A0469,KJ2021A0972)

Attribute reduction algorithm of numerical information system based on weighted neighborhood entropy

CHEN Baoguo¹, DENG Ming^{1 *}, CHEN Jinlin²

1. School of Computer Science, Huainan Normal University, Huainan 232038, Anhui, China;
2. College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, Jiangsu, China

Published:2024-02-01

摘要/Abstract

摘要： 在邻域粗糙集的属性约简中,每个属性被赋予相同的权重而不能更好地进行属性选择,针对这一问题,提出一种属性权重的邻域条件熵属性约简算法。通过条件属性与决策属性之间的相关系数评估条件属性的权重,基于权重方法提出一种改进的邻域关系,称为权重邻域关系,并提出相应的权重邻域粗糙集模型。以权重邻域粗糙集模型为基础,进一步提出权重邻域熵模型,理论证明权重邻域条件熵的单调性。通过权重邻域条件熵作为启发式函数提出一种新的数值型信息系统属性约简算法。试验结果表明,提出的属性约简算法具有更好的属性约简性能。

关键词: 数值型信息系统, 邻域粗糙集, 属性约简, 属性权重, 邻域熵

中图分类号:

TP18

陈宝国,邓明,陈金林. 基于权重邻域熵的数值型信息系统属性约简算法[J]. 山东大学学报 (工学版), 2024, 54(1): 33-44.

CHEN Baoguo, DENG Ming, CHEN Jinlin. Attribute reduction algorithm of numerical information system based on weighted neighborhood entropy[J]. Journal of Shandong University(Engineering Science), 2024, 54(1): 33-44.

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基于权重邻域熵的数值型信息系统属性约简算法

Attribute reduction algorithm of numerical information system based on weighted neighborhood entropy

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