OverNaN: NaN-Aware Oversampling for Imbalanced Learning with Meaningful Missingness
arXiv:2605.11525v1 Announce Type: new
Abstract: Missing values are routinely treated as defects to be eliminated through deletion or imputation prior to machine learning. In many applied domains, however, missingness itself carries information, reflec…