Abstract:

Given that the existing fuzzy clustering methods are just for existing data points, we put forward a new clustering method based on the original dataset to find a new cluster, called creative fuzzy c-means clustering algorithm (CFCM). The algorithm based on the FCM algorithm roughly determines the clustering center of the unknown cluster by introducing the observation point P as the prior knowledge of clustering, and defines the weight coefficient   λ to confine the influence degree of the point P on the formation of the new clustering center. Experimental results on artificial datasets and UCI classic datasets show that the proposed clustering algorithm not only has good clustering effect for the known data points, but can also creatively find out the new clustering center for certain zone which is only indicated by an observation point and does not contain any known data points, thus having potential applications in practice.

Key words: fuzzy clustering, creative fuzzy c-means clustering algorithm(CFCM), observation point