Abstract
In this chapter, we investigate the particular effects of the class imbalance problem on standard classifier methodologies and present the various methodologies that have been proposed as a remedy. The most interesting approach within the context of Artificial Immune Systems is the one related to the machine learning paradigm of one-class classification. One-Class Classification problems may be thought of as degenerated binary classification problems in which the available training instances originate exclusively from the under-represented class of patterns.
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Sotiropoulos, D.N., Tsihrintzis, G.A. (2017). Addressing the Class Imbalance Problem. In: Machine Learning Paradigms. Intelligent Systems Reference Library, vol 118. Springer, Cham. https://doi.org/10.1007/978-3-319-47194-5_4
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