Conformal prediction regions are imprecise highest density regions

Caprio, Michele; Sale, Yusuf und Hüllermeier, Eyke (15. July 2025): Conformal prediction regions are imprecise highest density regions. Proceedings of the Fourteenth International Symposium on Imprecise Probabilities: Theories and Applications, Bielefeld, Germany, 15. - 18. July, 2025. Destercke, Sébastien; Erreygers, Alexander; Nendel, Max; Riedel, Frank und Troffaes, Matthias C. M. (eds.) : Vol. 290 PMLR. pp. 47-59

Abstract

Recently, Cella and Martin proved how, under an assumption called <em>consonance</em>, a credal set (i.e. a closed and convex set of probabilities) can be derived from the conformal transducer associated with transductive conformal prediction. We show that the Imprecise Highest Density Region (IHDR) associated with such a credal set corresponds to the classical Conformal Prediction Region. In proving this result, we establish a new relationship between Conformal Prediction and Imprecise Probability (IP) theories, via the IP concept of a cloud. A byproduct of our presentation is the discovery that consonant plausibility functions are monoid homomorphisms, a new algebraic property of an IP tool.

• Item Type: Conference or Workshop Item (Paper)
• Faculties: Mathematics, Computer Science and Statistics > Computer Science > Artificial Intelligence and Machine Learning
• Subjects: 000 Computer science, information and general works > 004 Data processing computer science