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Inductive Conformal Prediction: A Straightforward Introduction with Examples in Python. (arXiv:2206.11810v3 [stat.ML] UPDATED)
June 29, 2022, 1:11 a.m. | Martim Sousa
stat.ML updates on arXiv.org arxiv.org
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. …
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