Handling Class Imbalance in Google Cluster Dataset Using a New Hybrid Sampling Approach
Author:
Publisher
Engineering and Technology Publishing
Subject
Artificial Intelligence,Computer Networks and Communications,Computer Science Applications,Information Systems,Software
Link
http://www.jait.us/uploadfile/2023/JAIT-V14N5-934.pdf
Reference25 articles.
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3. [3] V. López, A. Fernandez, S. Garcia, V. Palade, and F. Herrera, "An insight into classification with imbalanced data: Empirical results and current trends on using data intrinsic characteristics," Information Sciences, vol. 250, pp. 113-141, 2013.
4. [4] M. Galar, A. Fernandez, E. Barrenechea, H. Bustince, and F. Herrera, "A review on ensembles for the class imbalance problem: Bagging-, boosting-, and hybrid-based approaches," IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews), vol. 42, no. 4, pp. 463-484, July 2012.
5. [5] Cluster-data. [Online]. Available: https://github.com/google/cluster-data
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