Study on combining subtractive clustering with fuzzy c-means clustering

摘要

It is very sensitive to its initial value when we use fuzzy c-means (FCM) for fuzzy clustering. It will fall into local optimum solution if the enactment of initial value is not good, and it requests us to give the number of clustering before we use it. So we will use subtractive clustering to initialize the initial value of FCM before we use FCM to put up fuzzy clustering. Then we will gain the optimum solution, speed up the rate of convergence and need not give the cluster number beforehand.