Conformal Prediction under Hypergraphical Models - Artificial Intelligence Applications and Innovations Access content directly
Conference Papers Year : 2013

Conformal Prediction under Hypergraphical Models


Conformal predictors are usually defined and studied under the exchangeability assumption. However, their definition can be extended to a wide class of statistical models, called online compression models, while retaining their property of automatic validity. This paper is devoted to conformal prediction under hypergraphical models that are more specific than the exchangeability model. Namely, we define two natural classes of conformity measures for such hypergraphical models and study the corresponding conformal predictors empirically on benchmark LED data sets. Our experiments show that they are more efficient than conformal predictors that use only the exchangeability assumption.
Fichier principal
Vignette du fichier
978-3-642-41142-7_38_Chapter.pdf (1.45 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01459632 , version 1 (07-02-2017)





Valentina Fedorova, Alex Gammerman, Ilia Nouretdinov, Vladimir Vovk. Conformal Prediction under Hypergraphical Models. 9th Artificial Intelligence Applications and Innovations (AIAI), Sep 2013, Paphos, Greece. pp.371-383, ⟨10.1007/978-3-642-41142-7_38⟩. ⟨hal-01459632⟩
45 View
88 Download



Gmail Facebook X LinkedIn More