The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
To cite the vennabers package in publications use:
Kruse R (2026). vennabers: Venn-Abers Classification and Regression Calibration. R package version 1.0.0, https://github.com/RMKruse/vennabers.
Please also cite the methods you use. Venn-Abers predictors:
Vovk V, Petej I (2014). “Venn-Abers Predictors.” In Proceedings of the Thirtieth Conference on Uncertainty in Artificial Intelligence (UAI 2014), 829–838. doi:10.48550/arXiv.1211.0025.
Inductive and Cross Venn-Abers predictors:
Vovk V, Petej I, Fedorova V (2015). “Large-Scale Probabilistic Predictors with and without Guarantees of Validity.” In Advances in Neural Information Processing Systems 28, 892–900. doi:10.48550/arXiv.1511.00213.
Multiclass one-vs-one coupling:
Manokhin V (2017). “Multi-Class Probabilistic Classification Using Inductive and Cross Venn-Abers Predictors.” In Proceedings of the Sixth Workshop on Conformal and Probabilistic Prediction and Applications, volume 60 series Proceedings of Machine Learning Research, 228–240. https://proceedings.mlr.press/v60/manokhin17a.html.
CORP reliability diagrams:
Dimitriadis T, Gneiting T, Jordan A (2021). “Stable Reliability Diagrams for Probabilistic Classifiers.” Proceedings of the National Academy of Sciences, 118(8), e2016191118. doi:10.1073/pnas.2016191118.
Corresponding BibTeX entries:
@Manual{vennabers,
title = {{vennabers}: Venn-Abers Classification and Regression
Calibration},
author = {René-M. Kruse},
year = {2026},
note = {R package version 1.0.0},
url = {https://github.com/RMKruse/vennabers},
}
@InProceedings{VovkPetej2014,
title = {Venn-Abers Predictors},
author = {Vladimir Vovk and Ivan Petej},
booktitle = {Proceedings of the Thirtieth Conference on Uncertainty
in Artificial Intelligence (UAI 2014)},
pages = {829--838},
year = {2014},
publisher = {AUAI Press},
doi = {10.48550/arXiv.1211.0025},
}
@InProceedings{VovkPetejFedorova2015,
title = {Large-Scale Probabilistic Predictors with and without
Guarantees of Validity},
author = {Vladimir Vovk and Ivan Petej and Valentina Fedorova},
booktitle = {Advances in Neural Information Processing Systems 28},
pages = {892--900},
year = {2015},
doi = {10.48550/arXiv.1511.00213},
}
@InProceedings{Manokhin2017,
title = {Multi-Class Probabilistic Classification Using Inductive
and Cross Venn-Abers Predictors},
author = {Valery Manokhin},
booktitle = {Proceedings of the Sixth Workshop on Conformal and
Probabilistic Prediction and Applications},
series = {Proceedings of Machine Learning Research},
volume = {60},
pages = {228--240},
year = {2017},
publisher = {PMLR},
url = {https://proceedings.mlr.press/v60/manokhin17a.html},
}
@Article{DimitriadisGneitingJordan2021,
title = {Stable Reliability Diagrams for Probabilistic
Classifiers},
author = {Timo Dimitriadis and Tilmann Gneiting and Alexander I.
Jordan},
journal = {Proceedings of the National Academy of Sciences},
volume = {118},
number = {8},
pages = {e2016191118},
year = {2021},
doi = {10.1073/pnas.2016191118},
}
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.