Abstract
Proposed method of clustering is based on modified fuzzy c-means algorithm. In the paper features of input data are considered as linguistic variables. Any feature is described by set of fuzzy numbers. Thus, any input data representing a feature is a fuzzy number. The modified method allows finding the appropriate number of classes. Moreover, it uses improvements introducing in conventional fuzzy c-means algorithm increasing its robustness to the influence of outliers.
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Butkiewicz, B.S. (2005). Robust Fuzzy Clustering with Fuzzy Data. In: Szczepaniak, P.S., Kacprzyk, J., Niewiadomski, A. (eds) Advances in Web Intelligence. AWIC 2005. Lecture Notes in Computer Science(), vol 3528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11495772_13
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DOI: https://doi.org/10.1007/11495772_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26219-0
Online ISBN: 978-3-540-31900-9
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