On rival penalization controlled competitive learning for clustering with automatic cluster number selection

@article{Cheung2005OnRP,
  title={On rival penalization controlled competitive learning for clustering with automatic cluster number selection},
  author={Yiu-ming Cheung},
  journal={IEEE Transactions on Knowledge and Data Engineering},
  year={2005},
  volume={17},
  pages={1583-1588}
}
The existing rival penalized competitive learning (RPCL) algorithm and its variants have provided an attractive way to perform data clustering without knowing the exact number of clusters. However, their performance is sensitive to the preselection of the rival delearning rate. In this paper, we further investigate the RPCL and present a mechanism to control the strength of rival penalization dynamically. Consequently, we propose the rival penalization controlled competitive learning (RPCCL… CONTINUE READING
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