Abstract: Clustering algorithms based on grid have a drawback of low clustering precision,and most clustering algorithms based on density have high time complexity．In order to improve clustering performance,a cluster algorithm based on edge density distance was proposed in this paper．The new cluster algorithm makes new definitions of density and category．In the clustering process,data are divided into grids and some initial information is recorded firstly for the operation of finding k near points．Then in the process of finding a new clustering center,a method come from bucket sort is used,which makes it fast to find the clustering center．A subsequent procedure is to iteratively analyse k near points of one category to judge whether they are density accessible．Analysis in theory and result of experiments show that the proposed algorithm has both high quality in clustering result and low time complexity.

Key words: Cluster,Grid,Density,Caed,Dbscan,Kmeans