基于分层校验的多标签数据流概念漂移检测  

Concept Drift Detection of Multi-label Data Stream Based on Hierarchical Verification

作　　者：张永[1] 刘浩科 陈天祯 ZHANG Yong;LIU Haoke;CHEN Tianzhen(School of Computer and Information Technology,Liaoning Normal University,Dalian 116081)

机构地区：[1]辽宁师范大学计算机与信息技术学院,大连116081

出　　处：《模式识别与人工智能》2020年第3期202-210,共9页Pattern Recognition and Artificial Intelligence

基　　金：国家自然科学基金项目(No.61772252);辽宁省自然科学基金项目(No.2019-MS-216);辽宁省高等学校创新人才支持计划项目(No.LR2017044)资助。

摘　　要：现有的概念漂移检测方法大多集中于单标签数据流,难以满足多标签数据流概念漂移检测的需要,因此文中提出基于分层校验的多标签数据流概念漂移检测算法.算法包括检验层和校验层,检验层通过检测数据分布变化判断是否发生概念漂移,校验层通过判断标签混淆矩阵的变化程度验证是否真正发生概念漂移.在真实多标签数据集和合成多标签数据集上的实验表明,文中算法表现更优,可以有效检测概念漂移,提升分类性能.Most of the existing concept drift detection methods focus on single label data stream,and therefore they cannot meet the requirements of multi-label data stream concept drift detection.A concept drift detection algorithm of multi-label data stream based on hierarchical verification is proposed.The proposed algorithm consists of a test layer and a verification layer.The variation of data distribution is detected by the test layer to judge whether the concept drift occurs or not.The variation degree of tag confusion matrix is judged by the verification layer to verify whether the concept drift occurs indeed or not.Experiments on real multi-label and synthetic multi-label datasets indicate that the proposed algorithm detects the concept drift effectively and improves the classification performance.

关 键 词：概念漂移 多标签分类 数据流 分层校验 

分 类 号：TP181[自动化与计算机技术—控制理论与控制工程]