A fuzzy clustering algorithm based on adaptive city-block distances

This paper gives an adaptive version of the fuzzy clustering algorithm based on city-block distances. The proposed method gives a fuzzy partition and a prototype for each cluster by optimizing an adequacy criterion based on an adaptive city-block distance that changes at each algorithm´s iteration and is different from one cluster to another. Experiments with real data sets show the usefulness of this algorithm.