An Ε-insensitive Approach to Fuzzy Clustering

@inproceedings{ski2001AnA,
  title={An Ε-insensitive Approach to Fuzzy Clustering},
  author={Jacek Łęski},
  year={2001}
}
Fuzzy clustering can be helpful in finding natural vague boundaries in data. The fuzzy c-means method is one of the most popular clustering methods based on minimization of a criterion function. However, one of the greatest disadvantages of this method is its sensitivity to the presence of noise and outliers in the data. The present paper introduces a new ε-insensitive Fuzzy C-Means (εFCM) clustering algorithm. As a special case, this algorithm includes the well-known Fuzzy C-Medians method… CONTINUE READING
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