Closed
Description
sklearn.metrics introduces isclose() in https://github.com/scikit-learn/scikit-learn/blob/master/sklearn/metrics/ranking.py which can leave the unaware data practitioner with hours of debugging.
In very unbalanced classification, probabilities/scores can be very small and yet meaningful. This however will cause unexpected missing precision_recall points due to isclose treating values within 10e-6 as equal.
I'd suggest to place a warning about isclose in the documentation and also replace the absolute epsilon by a relative closeness comparison in order to avoid the problems with small probabilities in unbalanced classification.