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...

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Bibliographic Details
Published in:	Journal of King Saud University - Computer and Information Sciences
Main Author:	Wang Y.; Rosli M.M.; Musa N.; Wang L.
Format:	Article
Language:	English
Published:	King Saud bin Abdulaziz University 2024
Online Access:	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212189270&doi=10.1016%2fj.jksuci.2024.102253&partnerID=40&md5=1ce58b30e34c016e1273671a86217847

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