Abstract
A membership matrix of fuzzy c-mans clustering is associated with the corresponding fuzzy classification rules as membership functions defined on the whole space. In this paper such functions in fuzzy c-means and possibilistic clustering are directly derived using the calculus of variations. Consequently, the present formulation generalizes the ordinary fuzzy c-means and moreover related methods can be discussed within this framework.
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Miyamoto, S. (2007). Formulation of Fuzzy c-Means Clustering Using Calculus of Variations. In: Torra, V., Narukawa, Y., Yoshida, Y. (eds) Modeling Decisions for Artificial Intelligence. MDAI 2007. Lecture Notes in Computer Science(), vol 4617. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73729-2_19
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DOI: https://doi.org/10.1007/978-3-540-73729-2_19
Publisher Name: Springer, Berlin, Heidelberg
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