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Statistical classification is the problem of identifying the sub-population to which new observations belong, where the identity of the sub-population is unknown, on the basis of a training set of data containing observations whose sub-population is known. Therefore these classifications will show a variable behavior which can be studied by statistics.

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Convert predicted probabilities after downsampling to actual probabilities in classification

If I use undersampling in case of an unbalanced binary target variable to train a model, the prediction method calculates probabilities under the assumption of a balanced data set. I discovered two fo …
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1 vote

Calibration after up and downsampling

Maybe Platt's calibration is not flexible enough to give you a good conversion. You could try an isotonic regression model or simply an additive logit model.
tover's user avatar
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