计算机工程与应用2026，Vol.62Issue(12)：166-181,16.DOI:10.3778/j.issn.1002-8331.2510-0203
混合数据下基于Tsallis熵的集成因果特征选择算法
Ensemble Causal Feature Selection Algorithm Based on Tsallis Entropy for Mixed Data
摘要
Abstract
With the development of intelligent technologies,data has become high-dimensional.Causal feature selection,which is highly interpretable and robust,has been widely studied.It aims to select the feature set most relevant to the class variable,namely its parents and children(PC)and spouses(SP)sets,collectively referred to as the Markov blanket(MB)set,to reveal the causal relationships between features.In practical application scenarios,data often exhibits mixed distri-butions.Most existing causal feature selection algorithms focus only on single-type data and cannot be directly applied to mixed data.To address the above issue,this paper proposes an ensemble causal feature selection algorithm based on Tsallis entropy,called HTECFS,in mixed data scenarios.During the PC learning process,Tsallis mutual information,calculated directly from different forms of Tsallis entropy,is used to measure the correlation between features,avoiding potential information loss caused by data preprocessing.During the SP learning process,Tsallis conditional mutual information is used to test the SP features on the PC,and newly learned SP features are incorporated into the MB set to improve predic-tion accuracy of the model.Furthermore,multiple learning subspaces are constructed for independent MB learning to obtain an approximately globally optimal MB set.Moreover,a group optimization strategy is introduced to fuse the learning results,enhancing the globality and stability of the feature subset.Extensive tests on ten different types of datasets fully validate the effectiveness of the proposed algorithm.关键词
特征选择/因果关系/混合数据/群优化策略/Tsallis熵Key words
feature selection/causal relationship/mixed data/group optimization strategy/Tsallis entropy分类
信息技术与安全科学引用本文复制引用
刘子文,郑艺峰,陈新纪,魏葆雅,李国和..混合数据下基于Tsallis熵的集成因果特征选择算法[J].计算机工程与应用,2026,62(12):166-181,16.基金项目
国家自然科学基金面上项目(62376114) （62376114）
福建省自然科学基金面上项目(2026J001984) （2026J001984）
漳州市自然科学基金(ZZ2024J20) （ZZ2024J20）
中国石油大学(北京)克拉玛依校区科研启动基金(XQZX20240032) （北京）
克拉玛依市科技计划项目(2020CGZH0009) （2020CGZH0009）
福建省教育厅科技项目中青年重点项目(JZ230032) （JZ230032）
闽南师范大学校级研究生教学改革项目(YJG202416). （YJG202416）
