Hybrid oversampling technique for imbalanced pattern recognition: Enhancing performance with Borderline Synthetic Minority oversampling and Generative Adversarial Networks

Class imbalance problems (CIP) are one of the potential challenges in developing unbiased Machine Learning models for predictions. CIP occurs when data samples are not equally distributed between two or multiple classes. Several synthetic oversampling techniques have been introduced to balance the i...

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Главные авторы:	Md Manjurul Ahsan, Shivakumar Raman, Yingtao Liu, Zahed Siddique
Формат:	Artigo
Язык:	Inglês
Опубликовано:	Elsevier 2025-06-01
Серии:	Machine Learning with Applications
Предметы:	Imbalanced class Generative Adversarial Networks Synthetic Minority Oversampling Technique Borderline Synthetic Minority oversampling Machine learning Oversampling
Online-ссылка:	http://www.sciencedirect.com/science/article/pii/S2666827025000209
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