摘要： 模糊c-均值算法在进行模糊聚类的时候对初始值非常的敏感,初始值设置得不好,就会陷入局部最优解。该文在使用模糊c-均值之前利用减法聚类对其设置初始值,不但能够获得最优解,还能加快收敛速度,并且自动获得最佳的聚类个数。

关键词: 减法聚类, 模糊c-均值, 密度

Abstract: It is very sensitive to its initial value when one uses fuzzy c-means (FCM) to put up fuzzy clustering. It will get into local optimum solution if the enactment of initial value is not good. So the paper uses subtractive clustering to initialize the initial value of FCM before it uses FCM to put up fuzzy clustering. If one does these,it will gain the optimum solution,quicken the rate of convergence and need not to give the cluster number beforehand.

中图分类号: 

• TP18