Fuzzy Clustering and Robust Estimation

@inproceedings{Ohashi2008FuzzyCA,
  title={Fuzzy Clustering and Robust Estimation},
  author={Yasuo Ohashi},
  year={2008}
}
A modified version of the fuzzy k-means clustering is proposed for gelling the robustness (the resistance) against a few outliers. Some numerical examples are presented for illustrating the intuitively appropriate interpretation the modified method provides, and it is pointed out that the estimator of the typical value (the population mean) obtained in one-cluster case is equivalent to a kind of M -estimator. is added to (1)~(3), the resulting solution reduces to the usual partitioning of n… CONTINUE READING