南京师范大学学报（工程技术版）2024，Vol.24Issue(2)：34-42,9.DOI:10.3969/j.issn.1672-1292.2024.02.005
基于特征交互的层次分类在线流特征选择
Online Hierarchical Streaming Feature Selection Based on Feature Interaction
摘要
Abstract
In classification learning tasks in open dynamic environments,the data feature space is dynamic and there is a hierarchical structure in the labelling space.Existing hierarchical classification online streaming feature selection algorithms can select a superior subset of features,but these algorithms ignore the interactions that exist between the features.Therefore,this paper proposes a feature selection algorithm for hierarchical classification online streaming based on feature interaction.Firstly,a computational method based on hierarchical neighborhood dependency is designed to judge the feature interaction.Secondly,for hierarchical structure data,a neighborhood rough set model is defined on the basis of sibling relationships between different nodes in the hierarchical structure.Finally,the online streaming framework is designed for hierarchical classification with online importance analysis,online redundancy analysis and online interaction analysis for selecting the subset of features that are strongly correlated and have interaction.The proposed algorithm is experimentally verified on six hierarchical datasets to have superior comprehensive performance.关键词
在线流特征选择/层次分类/特征交互/兄弟策略/邻域粗糙集Key words
online streaming feature selection/hierarchical classification/feature interaction/sibling strategy/neighborhood rough set分类
信息技术与安全科学引用本文复制引用
孔令蔚,蔡林晟,林少杰,林耀进..基于特征交互的层次分类在线流特征选择[J].南京师范大学学报（工程技术版）,2024,24(2):34-42,9.基金项目
国家自然科学基金面上项目(62076116). （62076116）
