Acquisition ofZ-Number-Valued Clusters by Using a New Compound Function

Rafik Aziz Aliev, Witold Pedrycz, Babek Ghalib Guirimov, Oleg H. Huseynov · IEEE Transactions on Fuzzy Systems · 2020

A large number of clustering methods exist including deterministic, probabilistic, and fuzzy clustering. All these methods are devoted to handling different types of uncertainty. No studies have been encountered on clustering taking into account a confluence of probabilistic and fuzzy information. In the existing studies, the reliability of extracted knowledge is one of the important issues to be investigated. The concept ofZ-number arises as a formal construct that expresses reliability of information under bimodal distribution. In this article, we propose an approach to construction ofZ-number-valued clusters of a dataset for evaluation of reliability of extracted data-driven knowledge. Real-world applications are given that confirm the usefulness of the proposed method.

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