Conformal calibration. / Vovk, Vladimir; Petej, Ivan; Toccaceli, Paolo; Gammerman, Alex; Ahlberg, Ernst; Carlsson, Lars.

Proceedings of Machine Learning Research. ed. / Alex Gammerman; Vladimir Vovk; Zhiyuan Luo; Evgueni Smirnov; Giovanni Cherubin. Vol. 128 2020. p. 84-99.

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Abstract

Most existing examples of full conformal predictive systems, split conformal predictive systems, and cross-conformal predictive systems impose severe restrictions on the adaptation of predictive distributions to the test object at hand. In this paper we develop split conformal predictive systems that are fully adaptive. Our method consists in calibrating existing predictive systems; the input predictive system is not supposed to satisfy any properties of validity, whereas the output predictive system is guaranteed to be calibrated in probability.
Original languageEnglish
Title of host publicationProceedings of Machine Learning Research
EditorsAlex Gammerman, Vladimir Vovk, Zhiyuan Luo, Evgueni Smirnov, Giovanni Cherubin
Pages84-99
Number of pages16
Volume128
Publication statusPublished - Sep 2020

ID: 39085544