A Combined Priori and Purity Gaussian OverSampling Algorithm for Imbalanced Data Classification

The imbalanced data classification presents pervasive challenges in real-world data mining scenarios. To tackle these challenges, sampling techniques have emerged as effective approaches. However, the prevailing technique, SMOTE (Synthetic Minority Over-sampling Technique), and its derivatives make...

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Hlavní autoři:	Liangliang Tao, Huping Zhu, Qingya Wang, Yage Liang, Xiaozheng Deng
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2023-01-01
Edice:	IEEE Access
Témata:	Imbalanced learning priori purity Gaussian oversampling
On-line přístup:	https://ieeexplore.ieee.org/document/10322726/
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