A thresholded fuzzy c-means algorithm for semi-fuzzy clustering

摘要

In this paper, the problem of achieving “semi-fuzzy” or “soft” clustering of multidimensional data is discussed. A technique based on thresholding the results of the fuzzy c-means algorithm is introduced. The proposed approach is analysed and contrasted with the soft clustering method (see S. Z. Selim and M. A. Ismail, Pattern Recognition17, 559–568) showing the merits of the new method. Separation of clusters in the semi-fuzzy clustering context is introduced and the use of the proposed technique to measure the degree of separation is explained.