Szilágyi, L., Szilágyi, S.M. and Benyo, Z. (2008) A Thorough Analysis of the Suppressed Fuzzy C-Means Algorithm, Progress in Pattern Recognition, Image Analysis and Applications. Lecture Notes in Computer Science, 5197, 203-210.
http://dx.doi.org/10.1007/978-3-540-85920-8_25

has been cited by the following article:

• TITLE: A Fixed Suppressed Rate Selection Method for Suppressed Fuzzy C-Means Clustering Algorithm

  AUTHORS: Jiulun Fan, Jing Li

  KEYWORDS: Hard C-Means Clustering Algorithm, Fuzzy C-Means Clustering Algorithm, Suppressed Fuzzy C-Means Clustering Algorithm, Suppressed Rate

  JOURNAL NAME: Applied Mathematics, Vol.5 No.8, May 8, 2014

  ABSTRACT: Suppressed fuzzy c-means (S-FCM) clustering algorithm with the intention of combining the higher speed of hard c-means clustering algorithm and the better classification performance of fuzzy c-means clustering algorithm had been studied by many researchers and applied in many fields. In the algorithm, how to select the suppressed rate is a key step. In this paper, we give a method to select the fixed suppressed rate by the structure of the data itself. The experimental results show that the proposed method is a suitable way to select the suppressed rate in suppressed fuzzy c-means clustering algorithm.