A new imbalanced data oversampling method based on Bootstrap method and Wasserstein Generative Adversarial Network

A new imbalanced data oversampling method based on Bootstrap method and Wasserstein Generative Adversarial Network

Due to their high bias in favor of the majority class, traditional machine learning classifiers face a great challenge when there is a class imbalance in biological data. More recently, generative adversarial networks (GANs) have been applied to imbalanced data classification. For GANs, the distribu...

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Bibliographic Details
Main Authors: Binjie Hou, Gang Chen
Format: Article
Language:English
Published: AIMS Press 2024-02-01
Series:Mathematical Biosciences and Engineering
Subjects:
imbalanced data
generative adversarial networks (gans)
bootstrap method (bm)
data generation
probability distribution
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2024190?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2024190?viewType=HTML

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