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The likelihood interpretation of fuzzy data

Cattaneo, Marco E. G. V.

Authors

Marco E. G. V. Cattaneo



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 2194-5365
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Peer Reviewed Not Peer Reviewed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