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Applications of Conformal Regression on Real-world Industrial Use Cases using Crepes and MAPIE
AI Lab, Husqvarna Group, Stockholm, Sweden.
Jönköping University, Tekniska Högskolan, JTH, Avdelningen för datavetenskap, Jönköping AI Lab (JAIL).ORCID-id: 0000-0003-0274-9026
2023 (engelsk)Inngår i: Proceedings of the Twelfth Symposium on Conformal and Probabilistic Prediction with Applications / [ed] H. Papadopoulos, K. A. Nguyen, H. Boström & L. Carlsson, Proceedings of Machine Learning Research (PMLR) , 2023, Vol. 204, s. 147-165Konferansepaper, Publicerat paper (Fagfellevurdert)
Abstract [en]

Applying conformal prediction in real-world industrial use cases is rare, and publications are often limited to popular open-source data sets. This paper demonstrates two experimental use cases where the conformal prediction framework was applied to regression problems at Husqvarna Group with the two Python-based open-source platforms MAPIE and Crepes. The paper concludes by discussing lessons learned for the industry and some challenges for the conformal prediction community to address.

sted, utgiver, år, opplag, sider
Proceedings of Machine Learning Research (PMLR) , 2023. Vol. 204, s. 147-165
Serie
Proceedings of Machine Learning Research, E-ISSN 2640-3498 ; 204
Emneord [en]
Crepes, MAPIE, conformal regression, EnbPI, demand prediction, injection molding, manufacturing analytics, supply-chain, conformal predictive system
HSV kategori
Identifikatorer
URN: urn:nbn:se:hj:diva-62789Scopus ID: 2-s2.0-85178659649OAI: oai:DiVA.org:hj-62789DiVA, id: diva2:1807601
Konferanse
Twelfth Symposium on Conformal and Probabilistic Prediction with Applications, 13-15 September 2023, Limassol, Cyprus
Forskningsfinansiär
Knowledge FoundationTilgjengelig fra: 2023-10-27 Laget: 2023-10-27 Sist oppdatert: 2023-12-19bibliografisk kontrollert

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