A fuzzy k-modes algorithm for clustering categorical data

نویسندگان

  • Joshua Zhexue Huang
  • Michael K. Ng
چکیده

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.

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عنوان ژورنال:
  • IEEE Trans. Fuzzy Systems

دوره 7  شماره 

صفحات  -

تاریخ انتشار 1999