A research on fast FCM algorithm based on weighted sample

Abstract

To improve the computational performance of the fuzzy C-means (FCM) algorithm used in dataset clustering with large numbers, the concepts of the equivalent samples and the weighting samples based on eigenvalue distribution of the samples in the feature space were introduced and a novel fast cluster algorithm named weighted fuzzy C-means (WFCM) algorithm was put forward, which came from the traditional FCM algorithm. It was proved that the cluster results were equivalent in dataset with two different cluster algorithms: WFCM and FCM. Furthermore, the WFCM algorithm had better computational performance than the ordinary FCM algorithm. The experiment of the gray image segmentation showed that the WFCM algorithm is a fast and effective cluster algorithm.