Share Email Print

Proceedings Paper

Accelerated fuzzy C-means clustering algorithm
Author(s): Doron Hershfinkel; Its'hak Dinstein
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper 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.

Paper Details

Date Published: 14 June 1996
PDF: 12 pages
Proc. SPIE 2761, Applications of Fuzzy Logic Technology III, (14 June 1996); doi: 10.1117/12.243263
Show Author Affiliations
Doron Hershfinkel, Ben-Gurion Univ. of the Negev (Israel)
Its'hak Dinstein, Ben-Gurion Univ. of the Negev (Israel)

Published in SPIE Proceedings Vol. 2761:
Applications of Fuzzy Logic Technology III
Bruno Bosacchi; James C. Bezdek, Editor(s)

© SPIE. Terms of Use
Back to Top