Unsupervised Optimal Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
A new cluster validity index for the fuzzy c-mean
Pattern Recognition Letters
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Fuzzy cluster validation index based on inter-cluster proximity
Pattern Recognition Letters
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IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
On fuzzy cluster validity indices
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A cluster validity index for fuzzy clustering
Information Sciences: an International Journal
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Information Sciences: an International Journal
IEEE Transactions on Fuzzy Systems
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A cluster validity index for fuzzy clustering
Fuzzy Sets and Systems
Expert Systems with Applications: An International Journal
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Information Sciences: an International Journal
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Expert Systems with Applications: An International Journal
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A classification of cluster validity indexes based on membership degree and applications
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Information Sciences: an International Journal
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In this paper, the problem of traditional validity indices when applied to the Gustafson-Kessel (GK) clustering are reviewed. A new cluster validity index for the GK algorithm is proposed. This validity index is defined as the average value of the relative degrees of sharing of all possible pairs of fuzzy clusters in the system. It computes the overlap of each pair of fuzzy clusters by considering the degree of sharing of each data point in the overlap. The optimal number of clusters is obtained by minimizing the validity index. Experiments in which the proposed validity index and several traditional validity indices were applied to 6 data sets highlight the superior qualities of the proposed index. The results indicate that the proposed validity index is very reliable.