Note on the relationship between probabilistic and fuzzy clustering

S. T. Wang, Fu Lai Korris Chung, H. B. Shen, R. Q. Zhu

Research output: Journal article publicationJournal articleAcademic researchpeer-review

13 Citations (Scopus)


In this short communication, based on Renyi entropy measure, a new Renyi information based clustering algorithm A is presented. Algorithm A and the well-known fuzzy clustering algorithm FCM have the same clustering track. This fact builds the very bridge between probabilistic clustering and fuzzy clustering, and fruitful research results on Renyi entropy measure may help us to further understand the essence of fuzzy clustering.
Original languageEnglish
Pages (from-to)523-526
Number of pages4
JournalSoft Computing
Issue number7
Publication statusPublished - 1 Dec 2004


  • Fuzzy clustering
  • Probabilistic clustering
  • Renyi entropy

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Geometry and Topology


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