Problems in Fuzzy c-means and Its Possible Solutions

허경용; JINSEOK SEO; Lee， Im Geun

Journal of The Korea Society of Computer and Information

Abbr : JKSCI
2011, 16(1), pp.39-46
Publisher : The Korean Society Of Computer And Information
Research Area : Computer Science

허경용 ¹, JINSEOK SEO ², Lee， Im Geun ³

¹동의대학교
²동의대학교
³동의대학교

ABSTRACT

Clustering is one of the well-known unsupervised learning methods, in which a data set is grouped into some number of homogeneous clusters. There are numerous clustering algorithms available and they have been used in various applications. Fuzzy c-means (FCM), the most well-known partitional clustering algorithm, was established in 1970's and still in use. However, there are some unsolved problems in FCM and variants of FCM are still under development. In this paper, the problems in FCM are first explained and the available solutions are investigated, which is aimed to give researchers some possible ways of future research. Most of the FCM variants try to solve the problems using domain knowledge specific to a given problem. However, in this paper, we try to give general solutions without using any domain knowledge. Although there are more things left than discovered, this paper may be a good starting point for researchers newly entered into a clustering area.
KEYWORDS

Fuzzy c-means, Unsupervised learning, Partitional clustering, Problems in FCM
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KCI Citation (3)

KJC Korea
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