Abstract
In this short communication, based on Renyi entropy measure, a new Renyi information based clustering algorithm A is presented. Algorithm A and the well-known fuzzy clustering algorithm FCM have the same clustering track. This fact builds the very bridge between probabilistic clustering and fuzzy clustering, and fruitful research results on Renyi entropy measure may help us to further understand the essence of fuzzy clustering.
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This work was supported in part by the RGC CERG grant under project Hong Kong PolyU 5065/98E.
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Chung, K., Wang, S., Shen, H. et al. Note on the relationship between probabilistic and fuzzy clustering. Soft Computing 8, 523–526 (2004). https://doi.org/10.1007/s00500-003-0309-8
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DOI: https://doi.org/10.1007/s00500-003-0309-8