Learning from class-imbalanced data: Review of methods and applications
作者：
Highlights：
• 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.
摘要
•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.
论文关键词：Rare events,Imbalanced data,Machine learning,Data mining
论文评审过程：Received 6 September 2016, Revised 23 November 2016, Accepted 25 December 2016, Available online 30 December 2016, Version of Record 17 January 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2016.12.035
