Journal
FUZZY SETS AND SYSTEMS
Volume 141, Issue 2, Pages 301-317Publisher
ELSEVIER
DOI: 10.1016/S0165-0114(03)00072-1
Keywords
fuzzy clustering; fuzzy c-means; symbolic data; fuzzy data; mixed feature variables; dissimilarity measure
Ask authors/readers for more resources
This paper presents fuzzy clustering algorithms for mixed features of symbolic and fuzzy data. El-Sonbaty and Ismail proposed fuzzy c-means (FCM) clustering for symbolic data and Hathaway et al. proposed FCM for fuzzy data. In this paper we give a modified dissimilarity measure for symbolic and fuzzy data and then give FCM clustering algorithms for these mixed data types. Numerical examples and comparisons are also given. Numerical examples illustrate that the modified dissimilarity gives better results. Finally, the proposed clustering algorithm is applied to real data with mixed feature variables of symbolic and fuzzy data. (C) 2003 Elsevier B.V. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available