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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, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).ORCID iD: 0000-0003-0274-9026
2023 (English)In: 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, p. 147-165Conference paper, Published paper (Refereed)
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.

Place, publisher, year, edition, pages
Proceedings of Machine Learning Research (PMLR) , 2023. Vol. 204, p. 147-165
Series
Proceedings of Machine Learning Research, E-ISSN 2640-3498 ; 204
Keywords [en]
Crepes, MAPIE, conformal regression, EnbPI, demand prediction, injection molding, manufacturing analytics, supply-chain, conformal predictive system
National Category
Computer Sciences Information Systems
Identifiers
URN: urn:nbn:se:hj:diva-62789Scopus ID: 2-s2.0-85178659649OAI: oai:DiVA.org:hj-62789DiVA, id: diva2:1807601
Conference
Twelfth Symposium on Conformal and Probabilistic Prediction with Applications, 13-15 September 2023, Limassol, Cyprus
Funder
Knowledge FoundationAvailable from: 2023-10-27 Created: 2023-10-27 Last updated: 2023-12-19Bibliographically approved

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Löfström, Tuwe

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CiteExportLink to record
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