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Fuzzy c-means (FCM) clustering is the method for partitioning data into clusters by minimizing an objective function. Therefore, it is important to devise an objective function from which a simple clustering algorithm can be derived. An entropy term was introduced by S. Miyamoto in the FCM objective function. We proposed an objective function of the fuzzy counterpart of Gaussian mixture models (GMMs)...
This paper proposes an additional version of the fuzzy c-means based classifier (FCMC). The classifier FCMC-R treats relational data instead of object data. FCMCs use covariance structures to represent flexible shapes of clusters. Despite its effectiveness, the intense computation of covariance matrices is an impediment for classifying a set of high-dimensional feature data. In order to tackle with...
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