Cross-conformal predictive distributions

Vladimir Vovk, Ilia Nouretdinov, Valery Manokhin, Alexander Gammerman
Proceedings of the Seventh Workshop on Conformal and Probabilistic Prediction and Applications, PMLR 91:37-51, 2018.

Abstract

Conformal predictive systems are a recent modification of conformal predictors that output, in regression problems, probability distributions for labels of test observations rather than set predictions. The extra information provided by conformal predictive systems may be useful, e.g., in decision making problems. Conformal predictive systems inherit the relative computational inefficiency of conformal predictors. In this paper we discuss two computationally efficient versions of conformal predictive systems, which we call split conformal predictive systems and cross-conformal predictive systems, and discuss their advantages and limitations.

Cite this Paper

BibTeX
@InProceedings{pmlr-v91-vovk18a, title = {Cross-conformal predictive distributions}, author = {Vovk, Vladimir and Nouretdinov, Ilia and Manokhin, Valery and Gammerman, Alexander}, booktitle = {Proceedings of the Seventh Workshop on Conformal and Probabilistic Prediction and Applications}, pages = {37--51}, year = {2018}, editor = {Gammerman, Alex and Vovk, Vladimir and Luo, Zhiyuan and Smirnov, Evgueni and Peeters, Ralf}, volume = {91}, series = {Proceedings of Machine Learning Research}, month = {11--13 Jun}, publisher = {PMLR}, pdf = {http://proceedings.mlr.press/v91/vovk18a/vovk18a.pdf}, url = {https://proceedings.mlr.press/v91/vovk18a.html}, abstract = {Conformal predictive systems are a recent modification of conformal predictors that output, in regression problems, probability distributions for labels of test observations rather than set predictions. The extra information provided by conformal predictive systems may be useful, e.g., in decision making problems. Conformal predictive systems inherit the relative computational inefficiency of conformal predictors. In this paper we discuss two computationally efficient versions of conformal predictive systems, which we call split conformal predictive systems and cross-conformal predictive systems, and discuss their advantages and limitations.} }
Endnote
%0 Conference Paper %T Cross-conformal predictive distributions %A Vladimir Vovk %A Ilia Nouretdinov %A Valery Manokhin %A Alexander Gammerman %B Proceedings of the Seventh Workshop on Conformal and Probabilistic Prediction and Applications %C Proceedings of Machine Learning Research %D 2018 %E Alex Gammerman %E Vladimir Vovk %E Zhiyuan Luo %E Evgueni Smirnov %E Ralf Peeters %F pmlr-v91-vovk18a %I PMLR %P 37--51 %U https://proceedings.mlr.press/v91/vovk18a.html %V 91 %X Conformal predictive systems are a recent modification of conformal predictors that output, in regression problems, probability distributions for labels of test observations rather than set predictions. The extra information provided by conformal predictive systems may be useful, e.g., in decision making problems. Conformal predictive systems inherit the relative computational inefficiency of conformal predictors. In this paper we discuss two computationally efficient versions of conformal predictive systems, which we call split conformal predictive systems and cross-conformal predictive systems, and discuss their advantages and limitations.
APA
Vovk, V., Nouretdinov, I., Manokhin, V. & Gammerman, A.. (2018). Cross-conformal predictive distributions. Proceedings of the Seventh Workshop on Conformal and Probabilistic Prediction and Applications, in Proceedings of Machine Learning Research 91:37-51 Available from https://proceedings.mlr.press/v91/vovk18a.html.

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