Abstract
Fuzzy sets [68] were first proposed as a method of representing the uncertainty inherent in real data. This is an extension of conventional set theory. However, in the case of sets treated by conventional set theory, the elements in a set have to be judged as to whether the elements belong to the set or not. In the case of fuzzy sets, whether the elements belong to the set or not is unclear. In order to represent this mathematically, using the degree of the belongingness of each element to the set, fuzzy subsets are defined as follows:
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© 2006 Springer
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Sato-Ilic, M., Jain, L.C. (2006). Introduction to Fuzzy Clustering. In: Innovations in Fuzzy Clustering. Studies in Fuzziness and Soft Computing, vol 205. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-34357-1_1
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DOI: https://doi.org/10.1007/3-540-34357-1_1
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34356-1
Online ISBN: 978-3-540-34357-8
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