An adaptive fuzzy c-means algorithm with the L2 norm

Authors:
Nicomedes L. Cavalcanti Júnior;Francisco de A. T. de Carvalho
Affiliations:
Centro de Informática - CIn / UFPE, Recife, PE, Brasil;Centro de Informática - CIn / UFPE, Recife, PE, Brasil
Venue:
AI'05 Proceedings of the 18th Australian Joint conference on Advances in Artificial Intelligence
Year:
2005

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Abstract

An extension of the fuzzy c-means clustering algorithm based on an adaptive distance is presented. The proposed method furnishes a fuzzy partition and a prototype for each cluster by optimizing a criterion based on an adaptive L2 distance that changes at each algorithm iteration. Experiments with real and synthetic data sets show the usefulness of this method.