云南民族大学学报（自然科学版）2018，Vol.27Issue(1)：63-68,6.DOI:10.3969/j.issn.1672-8513.2018.01.014
基于随机平衡采样的不平衡数据流分类研究
A study of the classification of imbalanced data streams based on random balance sampling
摘要
Abstract
"Data stream" proposed by Henzinger is now widely used in the real world.However,imbalanced data streams seriously affect the functions of the traditional datastream classifiers.This paper proposes a new algorithm based on random balance sampling (RBS) to solve this problem.It then proposes an ensemble algorithm based on the random balance sampling of data streams for the problem of classifiers.The experiments based on synthetic and real-world datasets show that this new ensemble algorithm is fairly efficient for solving the problem of imbalanced data streams.关键词
不平衡数据/采样/数据流Key words
imbalanced data/sampling/data stream分类
信息技术与安全科学引用本文复制引用
袁磊,季梦遥..基于随机平衡采样的不平衡数据流分类研究[J].云南民族大学学报（自然科学版）,2018,27(1):63-68,6.基金项目
武汉大学自主科研项目(302-410500195,302-410500195). （302-410500195,302-410500195）
