Augmentation Based Synthetic Sampling and Ensemble Techniques for Imbalanced Data Classification
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-14903-0_15
Reference16 articles.
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3. Gameng, H.A., Gerardo, B.B., Medina, R.P.: Modified adaptive synthetic smote to improve classification performance in imbalanced datasets. In: 2019 IEEE 6th International Conference on Engineering Technologies and Applied Sciences (ICETAS), pp. 1–5. IEEE (2019)
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5. Jiang, X., Ge, Z.: Data augmentation classifier for imbalanced fault classification. IEEE Trans. Autom. Sci. Eng. 18(3), 1206–1217 (2020)
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