A new similarity measure based robust possibilistic c-means clustering algorithm

In this paper, we focus on the development of a new similarity measure based robust possibilistic c-means clustering (RPCM) algorithm which is not sensitive to the selection of initial parameters, robust to noise and outliers, and able to automatically determine the number of clusters. The proposed algorithm is based on an objective function of PCM which can be regarded as special case of similarity based robust clustering algorithms. Several simulations, including artificial and benchmark data sets, are conducted to demonstrate the effectiveness of the proposed algorithm.