Learning from Imbalanced Data Streams Using Rotation-Based Ensemble Classifiers
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-41456-5_60
Reference23 articles.
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2. Khamassi, I., Sayed Mouchaweh, M., Hammami, M., Ghédira, K.: Discussion and review on evolving data streams and concept drift adapting. Evol. Syst. 9(1), 1–23 (2018)
3. Shreya, S., Bernease, H., Aditya, G.P.: Rethinking streaming machine learning evaluation. arXiv (2022). https://doi.org/10.48550/arxiv.2205.11473
4. Czarnowski, I.: Weighted ensemble with one-class classification and over-sampling and instance selection (WECOI): an approach for learning from imbalanced data streams. J. Comput. Sci. 61(1), 101614 (2022). https://doi.org/10.1016/j.jocs.2022.101614
5. Benczúr, A.A., Kocsis, L., Pálovics, R.: Online machine learning in big data streams. arXiv (2018). https://doi.org/10.48550/ARXIV.1802.05872
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