Description: Based on the analysis on clustering algorithms especially on Density-Based clustering algorithm、Hierarchical-Based clustering algorithm and Partition-Based clustering algorithm, in this paper, a new kind of clustering algorithm that is clustering based on density and hierarchy is presented. This algorithm keeps the ability of density based clustering method’s good features, and it can reach high efficiency because of its linear time complexity, so it can be used in mining very large s. Both theory analysis and experimental results confirm that this algorithm can discover clusters with arbitrary shape and is insensitive to noise data. In the meanwhile, its executing efficiency is much higher than traditional DBSCAN algorithm.
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数据挖掘中的聚类算法研究.doc
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