most citedA survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework

165 citations · 165 across the 1 of their papers we have counts for

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cs.LG2022★ 165 cited

A survey on learning from imbalanced data streams: taxonomy, challenges, empirical study, and reproducible experimental framework

Gabriel Aguiar, Bartosz Krawczyk, Alberto Cano

Class imbalance poses new challenges when it comes to classifying data streams. Many algorithms recently proposed in the literature tackle this problem using a variety of data-leve…