Z-Number-Valued Clustering

Clustering is a large field of study devoted to knowledge extraction form data. Due to complexity of real data, deterministic, probabilistic, and fuzzy clustering problems exist. However, works devoted to taking into account combination of probabilistic and fuzzy information are scarce. For such problems, it is important to analyze reliability of extracted knowledge. For this aim, the concept of Z-number introduced by L. Zadeh may be used as formal construct to describe reliability under fuzziness and probabilistic uncertainty. This work is devoted to construction of Z-number-based clusters. Real-world problem is used to illustrate applicability of the proposed approach.