An Efficient Fuzzy C-Means Clustering Algorithm

Authors:
Ming-Chuan Hung;Don-Lin Yang
Affiliations:
-;-
Venue:
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Year:
2001

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Abstract

The Fuzzy C-Means (FCM) algorithm is commonly used for clustering.The performance of the FCM algorithm depends on the selection of the initial cluster center and/or the initial membership value.If a good initial cluster center that is close to the actual final clustercenter can be found, the FCM algorithm will converge very quickly and the processing time can be drastically.In this paper, we propose a novel algorithm for efficient clustering.This algorithm is a modified FCM called the psFCM algorithm, which significantly reduces the computation timerequired to partition a dataset into desired cluster.We find the actual cluster center by using a simplified set of the original complete dataset.It refines the initial value of the FCM algorithm to speed up the convergence time.Our Experiments show that the proposed psFCM algorithm isAlgorithm.We also demonstrate that the quality of the Proposed psFCM algorithm is the same as the FCM algorithm.