Jiaqi Han, Wenbing Huang, et al.
NeurIPS 2022
We previously discussed how classifiers based on logistic regression and decision trees can be used for predicting the class of an observation. Unfortunately, when such classifiers are trained on a dataset in which one of the response classes is rare, they can underestimate the probability of observing a rare event — the greater the imbalance, the greater this small-sample bias. This month, we illustrate how to mitigate the negative effect of class imbalance on the training of classifiers.
Jiaqi Han, Wenbing Huang, et al.
NeurIPS 2022
S. Ilker Birbil, Donato Maragno, et al.
AAAI 2023
Bo Zhao, Iordan Ganev, et al.
ICLR 2023
Jiawei Zhou, Tahira Naseem, et al.
NAACL 2021