Abstract:

Focusing on the fuzzy C means (FCM)algorithm’s shortcomings in terms of insufficiency caused by noisy sample points and data distribution characteristics to clustering results, FCM clustering is improved by the dataweighted strategy. For better effect, the improved algorithm limits clustering centres in high density areas,adjusts the clustering centres by density values adjustment, and highlight high density sample points’ influence in the clustering center adjustment. Simulation results with man made data and UCI real data show that the dataweighted FCM algorithm has higher accuracy without the increase of time complexity in contrast to the FCM algorithms.