NanBDOS: Adaptive and parameter-free borderline oversampling via natural neighbor search for class-imbalance learning-Reference-Cited by-同舟云学术

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NanBDOS: Adaptive and parameter-free borderline oversampling via natural neighbor search for class-imbalance learning

Published:2023-08 Issue: Volume:274 Page:110665
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Leng Qiangkui,Guo Jiamei,Jiao Erjie,Meng Xiangfu,Wang Changzhong

Funder

National Natural Science Foundation of China

Liaoning Technical University

Liaoning Revitalization Talents Program

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference61 articles.

1. DBIG-US: A two-stage under-sampling algorithm to face the class imbalance problem;Guzmán-Ponce;Expert Syst. Appl.,2021

2. Adaptive sampling using self-paced learning for imbalanced cancer data pre-diagnosis;Wang;Expert Syst. Appl.,2020

3. A new deep learning ensemble credit risk evaluation model with an improved synthetic minority oversampling technique;Shen;Appl. Soft Comput.,2021

4. Generative oversampling methods for handling imbalanced data in software fault prediction;Rathore;IEEE Trans. Reliab.,2022

5. An improved and random synthetic minority oversampling technique for imbalanced data;Wei;Knowl.-Based Syst.,2022

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1. CARBO: Clustering and rotation based oversampling for class imbalance learning;Knowledge-Based Systems;2024-09

2. HOOST: A novel hyperplane-oriented over-sampling technique for imbalanced fault detection of aero-engines;Knowledge-Based Systems;2024-09

3. Undersampling based on generalized learning vector quantization and natural nearest neighbors for imbalanced data;International Journal of Machine Learning and Cybernetics;2024-07-03

4. OBMI: oversampling borderline minority instances by a two-stage Tomek link-finding procedure for class imbalance problem;Complex & Intelligent Systems;2024-04-08

5. AWGAN: An adaptive weighting GAN approach for oversampling imbalanced datasets;Information Sciences;2024-03

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