Cross-conformal predictive distributions. / Vovk, Vladimir; Nouretdinov, Ilia; Manokhin, Valery; Gammerman, Alexander.

Proceedings of Machine Learning Research. ed. / Alex Gammerman; Vladimir Vovk; Zhiyuan Luo; Evgueni Smirnov; Ralf Peeters. Vol. 91 2018. p. 37-51.

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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.
Original languageEnglish
Title of host publicationProceedings of Machine Learning Research
EditorsAlex Gammerman, Vladimir Vovk, Zhiyuan Luo, Evgueni Smirnov, Ralf Peeters
Pages37-51
Number of pages15
Volume91
Publication statusPublished - Jun 2018
This open access research output is licenced under a Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

ID: 29977542