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Fuzzy clustering of fuzzy data based on robust loss functions and ordered weighted averaging
2019
Fuzzy sets and systems (Print)
In many real cases the data are not expressed in term of single values but are imprecise. In all these cases, standard clustering methods for single-valued data are unable to properly take into account the imprecise nature of the data. In this paper, by considering the Partitioning Around Medoids (PAM) approach in a fuzzy framework, we propose a fuzzy clustering method for imprecise data formalized in a fuzzy manner. In particular, in order to neutralize the negative effects of possible outlier
doi:10.1016/j.fss.2019.03.017
fatcat:qwofakybunef7mlcfeao4actta