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).
| Original language | English |
|---|---|
| Title of host publication | Proceedings of Machine Learning Research |
| Editors | Alex Gammerman, Vladimir Vovk, Zhiyuan Luo, Evgueni Smirnov, Ralf Peeters |
| Pages | 52-62 |
| Number of pages | 11 |
| Volume | 91 |
| Publication status | Published - Jun 2018 |
Keywords
- conformal prediction
- decision making
- predictive distributions
- regression
Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver