Referenced Items are not available for this document.
This correspondence describes extensions to the fuzzy k-means algorithm for clustering categorical data. By using a simple matching dissimilarity measure for categorical objects and modes instead of means for clusters, a new approach is developed, which allows the use of the k-means paradigm to efficiently cluster large categorical data sets. A fuzzy k-modes algorithm is presented and the effectiveness of the algorithm is demonstrated with experimental results
Published in:
Fuzzy Systems, IEEE Transactions on
(Volume:7
,
Issue:
4
)
Date of Publication: Aug 1999
- Page(s):
- 446 - 452
- ISSN :
- 1063-6706
- INSPEC Accession Number:
- 6350896
- Digital Object Identifier :
- 10.1109/91.784206
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 06 August 2002
- Issue Date :
- Aug 1999
- Sponsored by :
- IEEE Computational Intelligence Society
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