New clustering algorithm based on grid
一种新的基于网格的聚类算法*

This paper presented a new grid-based clustering algorithm which preprocessed the data using grid processing me-thod.The algorithm was capable of computing the radius of each grid according to the density dynamically.The required initial parameters for the clustering analysis were simplified by the previously processed data.The result of the experiments demonstrate that CABG is as accurate in discovering density-changeable clustering and handling of noise as DBSCAN,but CABG has higher clustering speed and less sensitivity to the initial parameters.