Xianghui Hu1, Yiming Tang2,3, Witold Pedrycz3,4, Jiuchuan Jiang5,*, Yichuan Jiang1,*
CMC-Computers, Materials & Continua, Vol.80, No.3, pp. 4917-4945, 2024, DOI:10.32604/cmc.2024.054775
- 12 September 2024
Abstract Traditional Fuzzy C-Means (FCM) and Possibilistic C-Means (PCM) clustering algorithms are data-driven, and their objective function minimization process is based on the available numeric data. Recently, knowledge hints have been introduced to form knowledge-driven clustering algorithms, which reveal a data structure that considers not only the relationships between data but also the compatibility with knowledge hints. However, these algorithms cannot produce the optimal number of clusters by the clustering algorithm itself; they require the assistance of evaluation indices. Moreover, knowledge hints are usually used as part of the data structure (directly replacing some clustering centers),… More >
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