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Fuzzy cluster validation index based on inter-cluster proximity
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DOI：10.1016/S0167-8655(03)00101-6.png)
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A new cluster validity index is proposed for fuzzy partitions obtained from Fuzzy C-Means algorithm. The proposed validity index exploits an inter-cluster proximity between fuzzy clusters. The inter-cluster proximity is used to measure the degree of overlap between clusters. A low proximity value indicates well-partitioned clusters. The best fuzzy c-partition is obtained by minimizing the inter-cluster proximity with respect to c. Well-known data sets are tested to show the effectiveness and reliability of the proposed index. (C) 2003 Elsevier B.V. All rights reserved.
Keyword:
cluster validity
proximity measure
fuzzy clustering
fuzzy C-means
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