Entropy-based Sampling Approaches for Multi-Class Imbalanced Problems-Reference-Cited by-同舟云学术

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Entropy-based Sampling Approaches for Multi-Class Imbalanced Problems

Published:2020-11-01 Issue:11 Volume:32 Page:2159-2170
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Li Lusi^ORCID,He Haibo^ORCID,Li Jie^ORCID

Funder

National Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Link

https://ieeexplore.ieee.org/ielam/69/9215208/8703114-aam.pdf

Cited by 51 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multi-Class Imbalance Classification Based on Data Distribution and Adaptive Weights;IEEE Transactions on Knowledge and Data Engineering;2024-10

2. Adaptive Semantic Information Extraction of Tibetan Opera Mask with Recall Loss;ACM Transactions on Asian and Low-Resource Language Information Processing;2024-07-26

3. E-SMOTE: Entropy Based Minority Oversampling for Heart Failure and AIDS Clinical Trails Analysis;2024 IEEE 48th Annual Computers, Software, and Applications Conference (COMPSAC);2024-07-02

4. A survey on imbalanced learning: latest research, applications and future directions;Artificial Intelligence Review;2024-05-09

5. Regularized Discrete Optimal Transport for Class-Imbalanced Classifications;Mathematics;2024-02-07

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