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The likelihood interpretation of fuzzy data

Cattaneo, Marco E. G. V.


Marco E. G. V. Cattaneo


© 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.

Journal Article Type Article
Publication Date 2017
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Peer Reviewed Not Peer Reviewed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
APA6 Citation Cattaneo, M. E. G. V. (2017). The likelihood interpretation of fuzzy data. Advances in Intelligent Systems and Computing, 456, 113-120. doi:10.1007/978-3-319-42972-4_14
Keywords Fuzzy sets, Foundations, Likelihood function, Measurement error, Fuzzy inference