A Simulation Study on The Behavior Analysis of The Degree of Membership in Fuzzy c-means Method
Takeo Okazaki, Ukyo Aibara, Lina Setiyani · IEIE Transactions on Smart Processing and Computing · 2015
Fuzzy c-means method is typical soft clustering, and requires a degree of membership that indicates the degree of belonging to each cluster at the time of clustering. Parameter values greater than 1 and less than 2 have been used by convention. According to the proposed datageneration scheme and the simulation results, some behaviors in the degree of “fuzziness” was derived.