Imbalance in Regression Datasets

arXiv:2402.11963v1 Announce Type: new
Abstract: For classification, the problem of class imbalance is well known and has been extensively studied. In this paper, we argue that imbalance in regression is an equally important problem which has so far been overlooked: Due to under- and over-representations in a data set's target distribution, regressors are prone to degenerate to naive models, systematically neglecting uncommon training data and over-representing targets seen often during training. We analyse this problem theoretically and use resulting insights …

abstract arxiv class classification cs.ai cs.lg data data set datasets distribution paper regression set type