A new cluster validity index is proposed for the validation of partitions of object data produced by the fuzzy c-means algorithm. The proposed validity index uses a variation measure and a separation measure between two fuzzy clusters. A good fuzzy partition is expected to have a low degree of variation and a large separation distance. Testing of the proposed index and nine previously formulated indices on well-known data sets shows the superior effectiveness and reliability of the proposed index in comparison to other indices and the robustness of the proposed index in noisy environments. © 2007 Elsevier Inc. All rights reserved.
CITATION STYLE
Zhang, Y., Wang, W., Zhang, X., & Li, Y. (2008). A cluster validity index for fuzzy clustering. Information Sciences, 178(4), 1205–1218. https://doi.org/10.1016/j.ins.2007.10.004
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