Note on the relationship between probabilistic and fuzzy clustering

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

doi:10.1007/s00500-003-0309-8

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 publication › Journal article › Academic research › peer-review

13 Citations (Scopus)

Abstract

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 language	English
Pages (from-to)	523-526
Number of pages	4
Journal	Soft Computing
Volume	8
Issue number	7
DOIs	https://doi.org/10.1007/s00500-003-0309-8
Publication status	Published - 1 Dec 2004

Keywords

Fuzzy clustering
Probabilistic clustering
Renyi entropy

ASJC Scopus subject areas

Software
Theoretical Computer Science
Geometry and Topology

More information

10.1007/s00500-003-0309-8

Cite this

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abstract = "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.",

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AU - Wang, S. T.

AU - Chung, Fu Lai Korris

AU - Shen, H. B.

AU - Zhu, R. Q.

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Y1 - 2004/12/1

N2 - 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.

AB - 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.

KW - Fuzzy clustering

KW - Probabilistic clustering

KW - Renyi entropy

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U2 - 10.1007/s00500-003-0309-8

DO - 10.1007/s00500-003-0309-8

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VL - 8

SP - 523

EP - 526

JO - Soft Computing

JF - Soft Computing

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Note on the relationship between probabilistic and fuzzy clustering

Abstract

Keywords

ASJC Scopus subject areas

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