A Novel Validity Index for Fuzzy Clustering

doi:10.3969/j.issn.1006-2475.2014.07.003

Abstract

Abstract: Combining compactness and separation information of fuzzy clustering, this paper proposes a novel validity index for clustering. This index can determine optimal partition and optimal number of clusters for fuzzy partitions obtained from the fuzzy C-means algorithm (FCM). Comparison experiment is done in one synthetic data set and four real datasets, and the results prove that this index has superior effectiveness.

Key words: fuzzy clustering, validity index, fuzzy C-means algorithm

CLC Number:

TP181

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TANG Guan-bao. A Novel Validity Index for Fuzzy Clustering[J]. Computer and Modernization, 2014, 0(7): 16-18+23.

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