A Novel Clustering Algorithm Based on Random Fuzziness Model

In the existing fuzzy clustering, membership is not easy to determine. In order to overcome the problem, we propose an efficient clustering algorithm based on random fuzziness model named RFKM, which can beset up mapping between randomness and fuzziness. This paper gives the operating steps of this method. Experiments prove that, compared with the FKM, the clustering method based on the random fuzziness can improve clustering effectively.