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Kernel Based Fuzzy Ant Clustering with Partition Validity
2006
2006 IEEE International Conference on Fuzzy Systems
We introduce a new swarm intelligence based algorithm for data clustering with a kernel-induced distance metric. Previously a swarm based approach using artificial ants to optimize the fuzzy c-means (FCM) criterion using the Euclidean distance was developed. However, FCM is not suitable for clusters which are not hyper-spherical and FCM requires the number of cluster centers be known in advance. The swarm based algorithm determines the number of cluster centers of the input data by using a
doi:10.1109/fuzzy.2006.1681695
dblp:conf/fuzzIEEE/GuH06
fatcat:cpja6rocs5d7df4mwtkdr4icba