IRIC: An R library for binary imbalanced classification. Imbalanced classification is a challenging issue in data mining and machine learning, for which a large number of solutions have been proposed. In this paper, we introduce an R library called IRIC, which integrates a wide set of solutions for imbalanced binary classification. IRIC not only provides a new implementation of some state-of-art techniques for imbalanced classification, but also improves the efficiency of model building using parallel techniques. The library and its source code are made freely available.
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References in zbMATH (referenced in 1 article , 1 standard article )
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- Bing Zhu; Zihan Gao; Junkai Zhao; Seppe K.L.M. van den Broucke: IRIC: An R library for binary imbalanced classification (2019) not zbMATH