电子学报2024，Vol.52Issue(3)：751-761,11.DOI:10.12263/DZXB.20220712
基于包络学习和分级结构一致性机制的不平衡集成算法
Imbalanced Ensemble Algorithm Based on Envelope Learning and Hierarchical Structure Consistency Mechanism
摘要
Abstract
Ensemble methods have become an important branch of imbalanced learning.However,the existing imbal-anced ensemble methods all rely on the original instances without considering the structure information of the instances,so their effectiveness is still limited.The research shows that the structure information of instances includes local and global structure information.In order to solve the above problem,this paper proposes an imbalanced ensemble algorithm based on deep instance envelope network(DIEN)and hierarchical structure consistency mechanism(HSCM).Considering the local manifold and global structure information,the algorithm generates high-quality deep envelope instances to achieve class bal-ance.Firstly,based on the instance neighborhood concatenation and fuzzy c-means clustering algorithm,the DIEN is de-signed to mine the structure information of instances,obtaining the deep envelope instances.Then,the local manifold struc-ture measure and global structure distribution measure are designed to construct the HSCM to enhance the distribution con-sistency of interlayer instances.Next,DIEN and HSCM are combined to construct the optimized deep instance envelope net-work—DH(DIEN with HSCM).Then,the base classifier is applied to the deep envelope instances.Finally,the bagging en-semble learning mechanism is designed to fuse the prediction results of the base classifier to obtain the final results.At the end of this paper,several groups of experiments are organized.More than 10 public datasets and representative related algo-rithms are used for verification.Experimental results show that the proposed algorithm is significantly better in four perfor-mance metrics,such as AUC(Area Under Curve)and F-measure.关键词
不平衡学习/包络学习/分级结构一致性机制/局部流形结构度量/全局结构分布度量Key words
imbalanced learning/envelope learning/hierarchical structure consistency mechanism/local manifold structure measure/global structure distribution measure分类
信息技术与安全科学引用本文复制引用
李帆,张小恒,李勇明,王品..基于包络学习和分级结构一致性机制的不平衡集成算法[J].电子学报,2024,52(3):751-761,11.基金项目
国家自然科学基金(No.61771080,No.U21A20448) （No.61771080,No.U21A20448）
中央高校基本科研业务费(No.2022CDJJJ-003) National Natural Science Foundation of China(No.61771080,No.U21A20448) （No.2022CDJJJ-003）
Central Uni-versity Basic Scientific Research Operation Cost Special Fund(No.2022CDJJJ-003) （No.2022CDJJJ-003）
