**Conformal predictive decision making.** / Vovk, Vladimir; Bendtsen, Claus.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Published

**Conformal predictive decision making.** / Vovk, Vladimir; Bendtsen, Claus.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Vovk, V & Bendtsen, C 2018, Conformal predictive decision making. in A Gammerman, V Vovk, Z Luo, E Smirnov & R Peeters (eds), *Proceedings of Machine Learning Research.* vol. 91, pp. 52-62. <http://proceedings.mlr.press/v91/vovk18b/vovk18b.pdf>

Vovk, V., & Bendtsen, C. (2018). Conformal predictive decision making. In A. Gammerman, V. Vovk, Z. Luo, E. Smirnov, & R. Peeters (Eds.), *Proceedings of Machine Learning Research *(Vol. 91, pp. 52-62) http://proceedings.mlr.press/v91/vovk18b/vovk18b.pdf

Vovk V, Bendtsen C. Conformal predictive decision making. In Gammerman A, Vovk V, Luo Z, Smirnov E, Peeters R, editors, Proceedings of Machine Learning Research. Vol. 91. 2018. p. 52-62

@inbook{72f92f7524234787822cc9add3792783,

title = "Conformal predictive decision making",

abstract = "This note explains how conformal predictive distributions can be used for the purpose of decision making. Namely, a major limitation of conformal predictive distributions is that, at this time, they are only applicable to regression problems, where the label is a real number; however, this does not prevent them from being used in a general problem of decision making. The resulting methodology of conformal predictive decision making is illustrated on a small benchmark data set. Our main theoretical observation is that there exists an asymptotically efficient predictive decision-making system which can be obtained by using our methodology (and therefore, satisfying the standard property of validity).",

keywords = "conformal prediction, decision making, predictive distributions, regression",

author = "Vladimir Vovk and Claus Bendtsen",

year = "2018",

month = jun,

language = "English",

volume = "91",

pages = "52--62",

editor = "Alex Gammerman and Vladimir Vovk and Zhiyuan Luo and Evgueni Smirnov and Ralf Peeters",

booktitle = "Proceedings of Machine Learning Research",

}

TY - CHAP

T1 - Conformal predictive decision making

AU - Vovk, Vladimir

AU - Bendtsen, Claus

PY - 2018/6

Y1 - 2018/6

N2 - This note explains how conformal predictive distributions can be used for the purpose of decision making. Namely, a major limitation of conformal predictive distributions is that, at this time, they are only applicable to regression problems, where the label is a real number; however, this does not prevent them from being used in a general problem of decision making. The resulting methodology of conformal predictive decision making is illustrated on a small benchmark data set. Our main theoretical observation is that there exists an asymptotically efficient predictive decision-making system which can be obtained by using our methodology (and therefore, satisfying the standard property of validity).

AB - This note explains how conformal predictive distributions can be used for the purpose of decision making. Namely, a major limitation of conformal predictive distributions is that, at this time, they are only applicable to regression problems, where the label is a real number; however, this does not prevent them from being used in a general problem of decision making. The resulting methodology of conformal predictive decision making is illustrated on a small benchmark data set. Our main theoretical observation is that there exists an asymptotically efficient predictive decision-making system which can be obtained by using our methodology (and therefore, satisfying the standard property of validity).

KW - conformal prediction

KW - decision making

KW - predictive distributions

KW - regression

M3 - Chapter

VL - 91

SP - 52

EP - 62

BT - Proceedings of Machine Learning Research

A2 - Gammerman, Alex

A2 - Vovk, Vladimir

A2 - Luo, Zhiyuan

A2 - Smirnov, Evgueni

A2 - Peeters, Ralf

ER -