Several formulations for graded possibilistic approach to fuzzy clustering
作者： Katsuhiro Honda , Hidetomo Ichihashi , Akira Notsu , Francesco Masulli , Stefano Rovetta
DOI: 10.1007/11908029_97
关键词:
摘要: Fuzzy clustering is a useful tool for capturing intrinsic structure of data sets. This paper proposes several formulations soft transition fuzzy memberships from probabilistic partition to possibilistic one. In the proposed techniques, free are given by introducing additional penalty term used in Possibilistic c-Means. The new features techniques demonstrated numerical experiments.
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