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Tutorial for using conformal prediction in KNIME
Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).ORCID iD: 0000-0003-0274-9026
Redfield AB, Sweden.
Jönköping University, School of Engineering, JTH, Department of Computing, Jönköping AI Lab (JAIL).ORCID iD: 0000-0003-0412-6199
2022 (English)In: Proceedings of the Eleventh Symposium on Conformal and Probabilistic Prediction with Applications: Volume 179: Conformal and Probabilistic Prediction with Applications, 24-26 August 2022, Brighton, UK / [ed] U. Johansson, H. Boström, K. A. Nguyen, Z. Luo & L. Carlsson, ML Research Press , 2022, Vol. 179, p. 4-23Conference paper, Published paper (Refereed)
Abstract [en]

KNIME is an end-to-end software platform for data science with an open source analytics platform for creating solutions and a commercial server solution for productionization. Redfield have previously developed nodes for conformal classification in KNIME. We introduce an extended conformal prediction package with added support for conformal regression. The conformal prediction package include class-conditional conformal classification, conformal regression and normalized conformal regression. The updated package also includes several new and updated nodes that focus on ease-of-use. This paper provide an introduction to various use cases for both simplified and advanced use as well as experiments to prove validity and showcase functionality. All examples are publicly available and the package is available through KNIME’s official software channels.

Place, publisher, year, edition, pages
ML Research Press , 2022. Vol. 179, p. 4-23
Series
Proceedings of Machine Learning Research, E-ISSN 2640-3498 ; 179
Keywords [en]
Conformal prediction, software implementations, KNIME Analytics Platform
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:hj:diva-58684Scopus ID: 2-s2.0-85164692291OAI: oai:DiVA.org:hj-58684DiVA, id: diva2:1705497
Conference
11th Symposium on Conformal and Probabilistic Prediction with Applications, 24-26 August 2022, Brighton, UK
Available from: 2022-10-24 Created: 2022-10-24 Last updated: 2023-08-17Bibliographically approved

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Löfström, TuweJohansson, Ulf

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