Recommended Reading
Drummond, C., & Holte, R. (2000). Exploiting the cost (in)sensitivity of decision tree splitting criteria. In Proceedings of the seventeenth international conference on machine learning (pp. 239–246).
Drummond, C., & Holte, R. (2005). Severe class imbalance: Why better algorithms aren’t the answer. In Proceedings of the sixteenth European conference of machine learning, LNAI (Vol. 3720, pp. 539–546).
Japkowicz, N., & Stephen, S. (2002). The class imbalance problem: A systematic study. Intelligent Data Analysis, 6(5), 429–450.
Ling, C. X., & Li, C. (1998). Data mining for direct marketing – Specific problems and solutions. In Proceedings of fourth international conference on Knowledge Discovery and Data Mining (KDD-98) (pp. 73–79).
Provost, F. (2000). Machine learning from imbalanced data sets 101. In Proceedings of the AAAI’2000 workshop on imbalanced data.
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Ling, C.X., Sheng, V.S. (2011). Class Imbalance Problem. In: Sammut, C., Webb, G.I. (eds) Encyclopedia of Machine Learning. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-30164-8_110
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DOI: https://doi.org/10.1007/978-0-387-30164-8_110
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