Hyperspherical possibilistic fuzzy c-means for high-dimensional data clustering

@article{Yan2009HypersphericalPF,
  title={Hyperspherical possibilistic fuzzy c-means for high-dimensional data clustering},
  author={Yang Yan and Lihui Chen},
  journal={2009 7th International Conference on Information, Communications and Signal Processing (ICICS)},
  year={2009},
  pages={1-5}
}
A possibilistic fuzzy c-means (PFCM)[1] has been proposed for clustering unlabeled data. It is a hybridization of possibilistic c-means (PCM) and fuzzy c-means (FCM), therefore it has been shown that PFCM is able to solve the noise sensitivity issue in FCM, and at the same time it helps to avoid coincident clusters problem in PCM with some numerical examples in low-dimensional data sets. In this paper, we conduct further evaluation of PFCM for high-dimensional data and proposed a revised… CONTINUE READING

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