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14 June 1996 Accelerated fuzzy C-means clustering algorithm
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Abstract
The proposed accelerated fuzzy c-means (AFCM) clustering algorithm is an improved version of the fuzzy c-mean (FCM) algorithm. Each iteration of the proposed algorithm consists of the regular operations of the FCM algorithm followed by an improvement stage. Once the cluster center locations are updated by the regular FCM algorithm operations, the improvement stage shifts each cluster center farther in its respective update direction. A number of possible strategies for the shift size control are studied and evaluated. The AFCM was applied to a number of data sets, using hundreds of different initial cluster center sets, yielding reductions of 37% to 65% in the number of iterations required for convergence by a similar FCM algorithm.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Doron Hershfinkel and Its'hak Dinstein "Accelerated fuzzy C-means clustering algorithm", Proc. SPIE 2761, Applications of Fuzzy Logic Technology III, (14 June 1996); https://doi.org/10.1117/12.243263
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