Conformal Prediction: a Unified Review of Theory and New Challenges

Matteo Fontana (), Gianluca Zeni and Simone Vantini

Papers from arXiv.org

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 predictions sets that are valid in a statistical sense also in in the finite sample case. The in-depth 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.

Date: 2020-05, Revised 2022-07
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Published in Bernoulli 29(1): 1-23 (February 2023)

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Persistent link: https://EconPapers.repec.org/RePEc:arx:papers:2005.07972

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