Learning from class-imbalanced data: Review of methods and applications

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• 作者：Guo Haixiang^a ; ^b ; ^c ; ¹ ; ^{faterdumk0732@sina.com} ; Li Yijing^a ; ^b ; ¹ ; ^{liyijing024@hotmail.com} ; ^{liyijing024@gmail.com} ; Jennifer Shang^d ; ^{shang@katz.pitt.edu} ; Gu Mingyun^a ; ^{550312686@qq.com} ; Huang Yuanyue^a ; ^{huangyuanyue1991@126.com} ; Gong Bing^e ; ^{gongbing1112@gmail.com}
• 关键词：Rare events ; Imbalanced data ; Machine learning ; Data mining
• 刊名：Expert Systems with Applications
• 出版年：2017
• 出版时间：1 May 2017
• 年：2017
• 卷：73
• 期：Complete
• 页码：220-239
• 全文大小：1977 K
• 卷排序：73

文摘

527 articles related to imbalanced data and rare events are reviewed. Viewing reviewed papers from both technical and practical perspectives. Summarizing existing methods and corresponding statistics by a new taxonomy idea. Categorizing 162 application papers into 13 domains and giving introduction. Some opening questions are discussed at the end of this manuscript.