Ella Barkan, Ibrahim Siddiqui, et al.
Computational And Structural Biotechnology Journal
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.
Ella Barkan, Ibrahim Siddiqui, et al.
Computational And Structural Biotechnology Journal
Bo Zhao, Nima Dehmamy, et al.
ICML 2025
S. Ilker Birbil, Donato Maragno, et al.
AAAI 2023
Raúl Fernández Díaz, Lam Thanh Hoang, et al.
ICLR 2025