Host: Japan Society for Fuzzy Theory and Intelligent Informatics (SOFT)
In this report, some fuzzy clustering methods are proposed based on Tsallis entropy-regularization. According to that conventional entropy-regularized fuzzy c-means (FCM) is obtained by regularzing Kmeans objective function with Shannon's entropy, Tsallis entropy-regularized FCM is proposed by regularizing Kmeans objective function with Tsallis entropy. The proposed method is different from Menard's method where Tsallis entropy is used not with Kmeans but with the standard FCM. Additionally, a variable controlling cluster size is introduced, and a maximizing model is proposed both for the proposed method and Menard's method.
