Conformal prediction
id:
conformal-prediction-165-2283249
title:
Conformal prediction
text:
Conformal prediction (CP) is a machine learning framework for uncertainty quantification that produces statistically valid prediction regions for any underlying point predictor only assuming exchangeability of the data. CP works by computing nonconformity scores on previously labeled data, and using these to create prediction sets on a new (unlabeled) test data point. A transductive version of CP was first proposed in 1998 by Gammerman, Vovk, and Vapnik, and since, several variants of conformal
brand slug:
wiki
category slug:
encyclopedia
description:
Statistical technique for producing prediction sets
original url:
https://en.wikipedia.org/wiki/Conformal_prediction
date created:
2021-09-15T14:13:04Z
date modified:
2024-08-29T05:56:46Z
main entity:
{"identifier":"Q108882887","url":"https://www.wikidata.org/entity/Q108882887"}
image:
fields total:
13
integrity:
15