A Tutorial on Conformal Prediction
Abstract
Conformal prediction uses past experience to determine precise levels of confidence in new predictions. Given an error probability ε, together with a method that makes a prediction ŷ of a label y, it produces a set of labels, typically containing ŷ, that also contains y with probability 1 – ε. Conformal prediction can be applied to any method for producing ŷ: a nearest-neighbor method, a support-vector machine, ridge regression, etc.
Cite
Text
Shafer and Vovk. "A Tutorial on Conformal Prediction." Journal of Machine Learning Research, 2008.Markdown
[Shafer and Vovk. "A Tutorial on Conformal Prediction." Journal of Machine Learning Research, 2008.](https://mlanthology.org/jmlr/2008/shafer2008jmlr-tutorial/)BibTeX
@article{shafer2008jmlr-tutorial,
title = {{A Tutorial on Conformal Prediction}},
author = {Shafer, Glenn and Vovk, Vladimir},
journal = {Journal of Machine Learning Research},
year = {2008},
pages = {371-421},
volume = {9},
url = {https://mlanthology.org/jmlr/2008/shafer2008jmlr-tutorial/}
}