A novel oversampling method based on Wasserstein CGAN for imbalanced classification

A novel oversampling method based on Wasserstein CGAN for imbalanced classification

Abstract Class imbalance is a crucial challenge in classification tasks, and in recent years, with the advancements in deep learning, research on oversampling techniques based on GANs has proliferated. These techniques have proven to be excellent in addressing the class imbalance issue by capturing...

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Bibliographic Details
Main Authors: Hongfang Zhou, Heng Pan, Kangyun Zheng, Zongling Wu, Qingyu Xiang
Format: Article
Language:English
Published: SpringerOpen 2025-02-01
Series:Cybersecurity
Subjects:
CGAN
Imbalanced data
Classification
Oversampling
K-means
$$k$$ k nearest neighbors
Online Access:https://doi.org/10.1186/s42400-024-00290-0
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https://doi.org/10.1186/s42400-024-00290-0

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