Stochastic configuration networks for imbalanced data classification-Reference-Cited by-同舟云学术

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Stochastic configuration networks for imbalanced data classification

Published:2022-04-29 Issue:10 Volume:13 Page:2843-2855
ISSN:1868-8071
Container-title:International Journal of Machine Learning and Cybernetics
language:en
Short-container-title:Int. J. Mach. Learn. & Cyber.

Author:

Dai Wei,Ning Chuanfeng,Nan Jing,Wang Dianhui

Funder

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

National Key R&D Program of China

State Key Laboratory of Synthetical Automation for Process Industries

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Software

Link

https://link.springer.com/content/pdf/10.1007/s13042-022-01565-z.pdf

Reference44 articles.

1. Nanni L, Fantozzi C, Lazzarini N (2015) Coupling different methods for overcoming the class imbalance problem. Neurocomputing 158:48–61

2. Malhotra R, Kamal S (2019) An empirical study to investigate oversampling methods for improving software defect prediction using imbalanced data. Neurocomputing 343:120–140

3. Abdi Y, Parsa S, Seyfari Y (2015) A hybrid one-class rule learning approach based on swarm intelligence for software fault prediction. Innovations Syst Softw Eng 11(4):289–301

4. Dhingra K, Yadav SK (2019) Spam analysis of big reviews dataset using fuzzy ranking evaluation algorithm and Hadoop. Int J Mach Learn Cybern 10(8):2143–2162

5. Gao X, Chen Z, Tang S, Zhang Y, Li J (2016) Adaptive weighted imbalance learning with application to abnormal activity recognition. Neurocomputing 173:1927–1935

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