The likelihood interpretation of fuzzy data

Cattaneo, Marco E. G. V.

Abstract

© Springer International Publishing Switzerland 2017. The interpretation of degrees of membership as statistical likelihood is probably the oldest interpretation of fuzzy sets. It allows in particular to easily incorporate fuzzy data and fuzzy inferences in statistical methods, and sheds some light on the central role played by extension principle and α-cuts in fuzzy set theory.

Citation

Cattaneo, M. E. G. V. (2017). The likelihood interpretation of fuzzy data. Advances in Intelligent Systems and Computing, 456, 113-120. https://doi.org/10.1007/978-3-319-42972-4_14

• Journal Article Type: Article
• Acceptance Date: Apr 21, 2016
• Online Publication Date: Jul 30, 2016
• Publication Date: 2017
• Deposit Date: Jun 17, 2016
• Journal: Soft methods for data science
• Print ISSN: 2194-5357
• Electronic ISSN: 2194-5357
• Publisher: Springer Verlag
• Peer Reviewed: Not Peer Reviewed
• Volume: 456
• Pages: 113-120
• Book Title: Advances in Intelligent Systems and Computing; Soft Methods for Data Science
• ISBN: 9783319429717; 9783319429724
• DOI: https://doi.org/10.1007/978-3-319-42972-4_14
• Keywords: Fuzzy sets, Foundations, Likelihood function, Measurement error, Fuzzy inference
• Public URL: https://hull-repository.worktribe.com/output/439787
• Contract Date: Jun 17, 2016