RIONIDA: A Novel Algorithm for Imbalanced Data Combining Instance-Based Learning and Rule Induction

The article presents the RIONIDA learning algorithm based on combination of two widely-used empirical approaches: rule induction and instance-based learning for imbalanced data classification. The algorithm is a substantial extension of the well-known RIONA algorithm developed for balanced data. RIONIDA is relatively fast and significantly outperforms the state-of-the-art algorithms analysed in the paper.