Possibilistic and fuzzy clustering methods for robust analysis of non-precise data
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Publication:2411254
DOI10.1016/j.ijar.2017.05.002zbMath1418.68204OpenAlexW2612907492MaRDI QIDQ2411254
Maria Brigida Ferraro, Paolo E. Giordani
Publication date: 20 October 2017
Published in: International Journal of Approximate Reasoning (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/11573/957287
Classification and discrimination; cluster analysis (statistical aspects) (62H30) Learning and adaptive systems in artificial intelligence (68T05) Reasoning under uncertainty in the context of artificial intelligence (68T37)
Related Items (4)
The integrated sigma-max system and its application in target recognition ⋮ Fuzzy data analysis and classification. Special issue in memoriam of Professor Lotfi A. Zadeh, father of fuzzy logic ⋮ Fuzzy clustering of fuzzy data based on robust loss functions and ordered weighted averaging ⋮ Partial possibilistic regression path modeling: handling uncertainty in path modeling
Uses Software
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