自动化学报2025，Vol.51Issue(5)：1131-1144,14.DOI:10.16383/j.aas.c240503
基于主动-被动增量集成的概念漂移适应方法
Concept Drift Adaptive Method Based on Active-Passive Incremental Ensemble
摘要
Abstract
A data stream refers to a set of data sequences that arrive continuously over time.Due to various influ-encing factors,the data distribution may change in an unpredictable manner over time during the continuous gener-ation of data streams,a phenomenon known as concept drift.After the drift occurs,the current model needs to re-spond promptly to the real-time distributional changes in the data stream and handle different types of concept drift efficiently,in order to avoid the degradation of the model generalization performance.Aiming at this problem,we propose a concept drift adaptation method based on the active-passive incremental ensemble(CDAM-APIE).Firstly,CDAM-APIE uses the online incremental ensemble strategy to construct a passive ensemble model,which makes real-time predictions on new samples to dynamically update the weights of the base model.It is beneficial for quickly responding to instantaneous changes in data distribution and enhancing the model's ability to adapt to concept drift.On this basis,an active basis model is constructed with incremental learning and concept drift detec-tion techniques to improve the robustness of the model under steady data stream states and the generalization per-formance after drift.The experimental results show that CDAM-APIE can respond to concept drift promptly and effectively improve the generalization performance of the model.关键词
概念漂移/数据流分类/增量学习/在线集成Key words
Concept drift/data stream classification/incremental learning/online ensemble引用本文复制引用
祁晓博,陈佳明,史颖,亓慧,郭虎升,王文剑..基于主动-被动增量集成的概念漂移适应方法[J].自动化学报,2025,51(5):1131-1144,14.基金项目
国家自然科学基金(62476157,U21A20513,62076154,62276157),山西省专利转化专项计划项目(202302009,202302012),山西省基础研究计划(自由探索类)项目(202103021223334),太原师范学院成果转化与技术转移基地(2023P003)资助Supported by National Natural Science Foundation of China(62476157,U21A20513,62076154,62276157),the Shanxi Prov-ince Patent Transformation Special Programs(202302009,202302012),the Basic Research Program(Free Exploration)of Shanxi Province(202103021223334),and Taiyuan Normal Uni-versity Achievement Transformation and Technology Transfer Base(2023P003) （62476157,U21A20513,62076154,62276157）
