计算机工程与应用2025，Vol.61Issue(19)：106-117,12.DOI:10.3778/j.issn.1002-8331.2501-0317
基于三支决策和邻域互信息的多标记特征选择方法
Multi-Label Feature Selection Based on Three-Way Decisions and Neighborhood Mutual Information
摘要
Abstract
Feature selection in multi-label learning is a critical step to enhance model performance and reduce computa-tional complexity.However,few multi-label feature selection techniques consider the impact of weight differences among labels on the feature space,and the issue of misclassification during the partition of uncertain samples is simultaneously neglected.To address the above issues,this work presents a multi-label feature selection method based on three-way deci-sions and neighborhood mutual information.Firstly,neighborhood mutual information is utilized to explore the intrinsic relationships of label weights in the feature space.Besides,a label significance measure,based on the neighborhood mutual information and label correlation is designed to depict the impact of labels on the feature space.Secondly,with the differ-ential processing of samples under multi-granularity,three-way decision theory is integrated into the multi-label feature selection to partition samples granularly and simplify the computational complexity.Finally,an objective function com-bining three-way decisions and neighborhood mutual information is constructed to measure the importance of features.Experimental analysis and performance comparison on eight real-world multi-label datasets further validate the feasibility and effectiveness of the proposed algorithm.关键词
特征选择/三支决策/粒计算/邻域互信息/多标记学习/标记权重/标记关系Key words
feature selection/three-way decisions/granular computing/neighborhood mutual information/multi-label learning/label weight/label relationship分类
信息技术与安全科学引用本文复制引用
谢觐平,钱文彬,蔡星星..基于三支决策和邻域互信息的多标记特征选择方法[J].计算机工程与应用,2025,61(19):106-117,12.基金项目
国家自然科学基金(62366019,61966016) （62366019,61966016）
江西省自然科学基金(20224BAB202020). （20224BAB202020）
