HS-Gen: a hypersphere-constrained generation mechanism to improve synthetic minority oversampling for imbalanced classification

HS-Gen: a hypersphere-constrained generation mechanism to improve synthetic minority oversampling for imbalanced classification

Abstract Mitigating the impact of class-imbalance data on classifiers is a challenging task in machine learning. SMOTE is a well-known method to tackle this task by modifying class distribution and generating synthetic instances. However, most of the SMOTE-based methods focus on the phase of data se...

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Bibliographic Details
Main Authors: Zuowei He, Jiaqing Tao, Qiangkui Leng, Junchang Zhai, Changzhong Wang
Format: Article
Language:English
Published: Springer 2022-12-01
Series:Complex & Intelligent Systems
Subjects:
Imbalanced classification
Synthetic oversampling
SMOTE
Generation mechanism
Hypersphere constraint
Online Access:https://doi.org/10.1007/s40747-022-00938-9

Internet

https://doi.org/10.1007/s40747-022-00938-9

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