Abstract
In this work we provide a review of basic ideas and novel developments about Conformal Prediction — an innovative distribution-free, non-parametric forecasting method, based on minimal assumptions — that is able to yield in a very straightforward way prediction sets that are valid in a statistical sense also in the finite sample case. The discussion provided in the paper covers the theoretical underpinnings of Conformal Prediction, and then proceeds to list the more advanced developments and adaptations of the original idea.
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