Publication
Nature Methods
Paper

The class imbalance problem

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Abstract

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.

Date

15 Oct 2021

Publication

Nature Methods

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