2000 Volume 12 Issue 5 Pages 686-695
The aim of the present paper is to discuss fuzzy clustering of data with interval uncertainties. Two basic methods of standard fuzzy c-means and entropy method are considered. When handling the data with interval uncertainties, we consider two types of distances between a point and a set:nearest neighbor and farthest neighbor. Using these distances, clustering methods for data with interval uncertainties are proposed. Exact optimization algorithms for cluster centers based on the two distances are developed. In numerical examples, results for the data with interval uncertainties and without the uncertainties are compared.
