Fuzzy Clustering : Insights and a New Approach

@inproceedings{Klawonn2006FuzzyC,
  title={Fuzzy Clustering : Insights and a New Approach},
  author={Frank Klawonn},
  year={2006}
}
Fuzzy clustering extends crisp clustering in the sense that objects can belong to various clusters with different membership degrees at the same time, whereas crisp or deterministic clustering assigns each object to a unique cluster. The standard approach to fuzzy clustering introduces the so-called fuzzifier which controls how much clusters may overlap. In this paper we illustrate, how this fuzzifier can help to reduce the number of undesired local minima of the objective function that is… CONTINUE READING

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