[1]QING Ming,SUN Xiaomei.A new clustering effectiveness function: fuzzy entropy of fuzzy partition[J].CAAI Transactions on Intelligent Systems,2015,10(1):75-80.[doi:10.3969/j.issn.1673-4785.201410004]
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A new clustering effectiveness function: fuzzy entropy of fuzzy partition

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 10 Number of periods: 2015 1 Page number: 75-80 Column: 学术论文—人工智能基础 Public date: 2015-03-25
Title:
A new clustering effectiveness function: fuzzy entropy of fuzzy partition
Author(s):
QING Ming1;  SUN Xiaomei2
1. School of Mathematics, Southwest Jiaotong University, Chengdu 610031, China;
2. Department of Mathematical and Physical Science, Henan Institution of Engineering, Zhengzhou 451191, China
Keywords:
fuzzy C-means clustering; fuzzy entropy of fuzzy partition; clustering effectiveness; clustering analysis; fuzzy partition; fuzzy entropy; entropy function; fuzzy set
CLC:
TPO235
DOI:
10.3969/j.issn.1673-4785.201410004
Abstract:
In this paper, the determination that whether a fuzzy clustering analysis result is reasonable or not is decided by the effectiveness of fuzzy clustering and its core is the construction of fuzzy clustering effectiveness function. This paper proposed a new concept of fuzzy entropy for a fuzzy partition to describe fuzzy degree of a fuzzy partition based on an order relation. Fuzzy entropy for a fuzzy partition is also considered as a clustering effectiveness function because some existing fuzzy clustering effectiveness functions are based on fuzzy partition of data sets. The experiments demonstrated that it is reasonable and practicable to utilize fuzzy entropy for a fuzzy partition as the effectiveness function of a fuzzy clustering.
References:
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