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.

Research output: Chapter in Book/Report/Conference proceedingChapter

Published

Standard

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.

Research output: Chapter in Book/Report/Conference proceedingChapter

Harvard

Vovk, V, Nouretdinov, I, Manokhin, V & Gammerman, A 2018, Cross-conformal predictive distributions. in A Gammerman, V Vovk, Z Luo, E Smirnov & R Peeters (eds), Proceedings of Machine Learning Research. vol. 91, pp. 37-51. <http://proceedings.mlr.press/v91/vovk18a.html>

APA

Vovk, V., Nouretdinov, I., Manokhin, V., & Gammerman, A. (2018). Cross-conformal predictive distributions. In A. Gammerman, V. Vovk, Z. Luo, E. Smirnov, & R. Peeters (Eds.), Proceedings of Machine Learning Research (Vol. 91, pp. 37-51) http://proceedings.mlr.press/v91/vovk18a.html

Vancouver

Vovk V, Nouretdinov I, Manokhin V, Gammerman A. Cross-conformal predictive distributions. In Gammerman A, Vovk V, Luo Z, Smirnov E, Peeters R, editors, Proceedings of Machine Learning Research. Vol. 91. 2018. p. 37-51

Author

Vovk, Vladimir ; Nouretdinov, Ilia ; Manokhin, Valery ; Gammerman, Alexander. / Cross-conformal predictive distributions. Proceedings of Machine Learning Research. editor / Alex Gammerman ; Vladimir Vovk ; Zhiyuan Luo ; Evgueni Smirnov ; Ralf Peeters. Vol. 91 2018. pp. 37-51

BibTeX

@inbook{6135299b84c94946827427980fba678f,
title = "Cross-conformal predictive distributions",
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.",
keywords = "conformal prediction, cross-conformal prediction, inductive conformal prediction, predictive distributions, split conformal prediction, regression",
author = "Vladimir Vovk and Ilia Nouretdinov and Valery Manokhin and Alexander Gammerman",
year = "2018",
month = jun,
language = "English",
volume = "91",
pages = "37--51",
editor = "Alex Gammerman and Vladimir Vovk and Zhiyuan Luo and Evgueni Smirnov and Ralf Peeters",
booktitle = "Proceedings of Machine Learning Research",

}

RIS

TY - CHAP

T1 - Cross-conformal predictive distributions

AU - Vovk, Vladimir

AU - Nouretdinov, Ilia

AU - Manokhin, Valery

AU - Gammerman, Alexander

PY - 2018/6

Y1 - 2018/6

N2 - 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.

AB - 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.

KW - conformal prediction

KW - cross-conformal prediction

KW - inductive conformal prediction

KW - predictive distributions

KW - split conformal prediction

KW - regression

M3 - Chapter

VL - 91

SP - 37

EP - 51

BT - Proceedings of Machine Learning Research

A2 - Gammerman, Alex

A2 - Vovk, Vladimir

A2 - Luo, Zhiyuan

A2 - Smirnov, Evgueni

A2 - Peeters, Ralf

ER -