Grouping-based Oversampling in Kernel Space for Imbalanced Data Classification

doi:10.1016/j.patcog.2022.108992

	Grouping-based Oversampling in Kernel Space for Imbalanced Data Classification
	Ren, Jinjun1,2 ; Wang, Yuping 1; Cheung, Yiu-ming 3; Gao, Xiao-Zhi 4; Guo, Xiaofang 5
	2023
发表期刊	PATTERN RECOGNITION
卷号	133
摘要	The class-imbalanced classification is a difficult problem because not only traditional classifiers are more biased towards the majority classes and inclined to generate incorrect predictions, but also the existing algorithms often have difficulty tackling this kind of problem with the class overlapping. Oversampling is a widely used and effective method to obtain balanced samples for imbalanced data, but the existing oversampling methods usually result in more serious class overlapping due to improper choice of the ref-erence samples. To circumvent this shortcoming, according to the different possibilities of minority class samples appearing in the overlapping regions in the feature space, a grouping scheme for the minor-ity class samples is first designed to identify the overlapping region samples. Then, a new oversampling method based on this grouping scheme is proposed to make the new samples far away from the over-lapping region and rectify the decision boundary properly. Subsequently, a new effective classification algorithm is developed for imbalanced data. Extensive experiments show that the proposed algorithm is superior to the seventeen benchmark algorithms in terms of three performance metrics, especially on high imbalance ratio data sets. (c) 2022 Elsevier Ltd. All rights reserved.
关键词	Imbalanced data classification Kernel method Support vector machine Oversampling
DOI	10.1016/j.patcog.2022.108992
收录类别	SCIE ; EI
ISSN	0031-3203
语种	英语
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000863094500004
出版者	ELSEVIER SCI LTD
EI入藏号	20225113269148
EI主题词	Support vector machines
EI分类号	716.1 Information Theory and Signal Processing ; 723 Computer Software, Data Handling and Applications ; 903.1 Information Sources and Analysis ; 921 Mathematics
原始文献类型	Article
EISSN	1873-5142
引用统计	被引频次：20[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.lzufe.edu.cn/handle/39EH0E1M/32984
专题	信息工程与人工智能学院
作者单位	1.Xidian Univ, Sch Comp Sci & Technol, Xian 710071, Shaanxi, Peoples R China; 2.Lanzhou Univ Finance & Econ, Sch Infomat Engn, Lanzhou 730101, Gansu, Peoples R China; 3.Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Peoples R China; 4.Univ Eastern Finland, Sch Comp, Kuopio, Finland; 5.Xian Technol Univ, Sch Sci, Xian 710021, Peoples R China
第一作者单位	兰州财经大学
推荐引用方式 GB/T 7714	Ren, Jinjun,Wang, Yuping,Cheung, Yiu-ming,et al. Grouping-based Oversampling in Kernel Space for Imbalanced Data Classification[J]. PATTERN RECOGNITION,2023,133.
APA	Ren, Jinjun,Wang, Yuping,Cheung, Yiu-ming,Gao, Xiao-Zhi,&Guo, Xiaofang.(2023).Grouping-based Oversampling in Kernel Space for Imbalanced Data Classification.PATTERN RECOGNITION,133.
MLA	Ren, Jinjun,et al."Grouping-based Oversampling in Kernel Space for Imbalanced Data Classification".PATTERN RECOGNITION 133(2023).