Abstract:The fuzzy C-means clustering algorithm is the most widely used clustering algorithm, but it still remains sensitive to outliers and dependent on initial centers and other issues. Therefore, this paper presents an improving fuzzy clustering algorithm based on sample weighting, the algorithm can get more accurate initial center points and remove noise. At the same time, to the weakness of the clustering algorithm in Weka system and the clustering problem is extensive in the field of data mining, this paper makes the platform the secondary development, researches the traditional FCM algorithm and improving algorithm. The study finds that the improving algorithm makes the clustering results stable, obtain the accurate clustering results and improve the accuracy of the algorithm.