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Conference Papers Year : 2020

Conformal multi-target regression using neural networks


Multi-task learning is a domain that is still not fully studied in the conformal prediction framework, and this is particularly true for multi-target regression. Our work uses inductive conformal prediction along with deep neural networks to handle multi-target regression by exploring multiple extensions of existing single-target non-conformity measures and proposing new ones. This paper presents our approaches to work with conformal prediction in the multiple regression setting, as well as the results of our conducted experiments.
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hal-03029473 , version 1 (28-11-2020)


  • HAL Id : hal-03029473 , version 1


Soundouss Messoudi, Sébastien Destercke, Sylvain Rousseau. Conformal multi-target regression using neural networks. 9th Symposium on Conformal and Probabilistic Prediction with Applications (COPA 2020), Aug 2020, Verone (virtual), Italy. pp.65-83. ⟨hal-03029473⟩
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