Improving clustering-based and adaptive position-aware interpolation oversampling for imbalanced data classification

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Improving clustering-based and adaptive position-aware interpolation oversampling for imbalanced data classification

Class imbalance is one of the most significant difficulties in modern machine learning. This is because of the inherent bias of standard classifiers toward favoring majority instances while often ignoring minority instances. Interpolation-based oversampling techniques are among the most popular solu...

书目详细资料
发表在:	JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES
Main Authors:	Wang, Yujiang; Rosli, Marshima Mohd; Musa, Norzilah; Wang, Lei
格式:	文件
语言:	English
出版:	SPRINGERNATURE 2024
主题:	Computer Science
在线阅读:	https://www-webofscience-com.uitm.idm.oclc.org/wos/woscc/full-record/WOS:001410486900001

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