Modified Global K'-means Algorithm and Its Application to Data Clustering

In order to solve the problems of the initialization of clustering centers,determination of the number of clustering centers,and avoidance of dead-unit and so on,a modified global E-means algorithm(MGK'M) is proposed.The improved algorithm can be used not only to calculate its starting point by the auxiliary cluster function,but also to find the actual number of clusters by using the cost-function without preset the number of clusters.At the same time,it can avoid the dead-unit problem.The improved algorithm is used for clustering of actual data sets.Experiment results demonstrate that the proposed algorithm can get better clustering results compared with the modified global K-means algorithm and K-means algorithm.