Abstract
A method, named XHJ-method, is proposed in this letter to determine the number of clusters of a data set, which incorporates with the Fuzzy Reinforced Learning Vector Quantization (FRLVQ) technique. The simulation results show that this new method works well for the traditional iris data and an artificial data set, which contains un-equally sized and spaced clusters.
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Supported by the National Natural Science Foundation of China (No.60172065).
Communication author: Ji Zhen, born in 1973, male, Ph.D., professor. The Faculty of Information Engineering, Shenzhen University, Shenzhen 518060, China.
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Xu, W., Huang, Q., Ji, Z. et al. Determine optimum number of compact overlapped clusters using FRLVQ technique. J. of Electron.(China) 22, 676–680 (2005). https://doi.org/10.1007/BF02687850
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DOI: https://doi.org/10.1007/BF02687850