基于扩展和网格的多密度聚类算法

提出了网格密度可达的聚类概念和边界处理技术，并在此基础上提出一种基于扩展的多密度网格聚类算法。该算法使用网格技术提高聚类的速度，使用边界处理技术提高聚类的精度，每次聚类均从最高的密度单元开始逐步向周围扩展形成聚类．实验结果表明，该算法能有效地对多密度数据集和均匀密度数据集进行聚类，具有聚类精度高等优点．

Grid-based and Extend-based Clustering Algorithm for Multi-density

The clustering concept of grid density reachability and boundary point extraction technique are proposed.Based on that,a grid-based and extendbased clustering algorithm for multi-density data sets(GECM) is developed.In GECM,grid-based method is used to improve speed of clustering,and boundary point extraction technique is used to improve quality of clustering.A clustering starts with the highest density cell and then extends to its neighbors to form a cluster.Experiment results show that the proposed algorithm is efficient and effective for multi-density and uniformity density data sets with noises.