In classification problems, the proportion of cases in each class largely determines the base rate of the predictions produced by the model. Therefore if you use sampling techniques that change this proportion, there is a good chance you will want to rescale / calibrate your predictions before using them in the wild.
Originally from KDnuggets https://ift.tt/3mngn84
source https://365datascience.weebly.com/the-best-data-science-blog-2020/undersampling-will-change-the-base-rates-of-your-models-predictions
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