Potential function partial weighted fuzzy C-mean (PWFCM) clustering method

A new clustering method-the potential function partial weighted fuzzy C-mean (PWFCM) clustering method is presented. In this method samples' typicality is decided by a potential distribution function in sample feature space. According to a sample set, the problem of how to adaptively determine the weighted matrix W is also discussed. Because the different influences on the partition by different samples in the feature space is considered, the proposed method can effectively partition perplexing data sets. Finally, the results of two experiments are compared with satisfactory results.