Inductive Conformal Prediction: A Straightforward Introduction with Examples in Python. (arXiv:2206.11810v2 [stat.ML] UPDATED)

Inductive Conformal Prediction (ICP) is a set of distribution-free and model
agnostic algorithms devised to predict with a user-defined confidence with
coverage guarantee. Instead of having point predictions, i.e., a real number in
the case of regression or a single class in multi class classification, models
calibrated using ICP output an interval or a set of classes, respectively. ICP
takes special importance in high-risk settings where we want the true output to
belong to the prediction set with high probability. …

arxiv examples inductive introduction ml prediction python