Hierarchical method : create a hierarchical decomposition of the set of data objects . 層次的方法:對給定數據對象集合進行層次分解。
The basic idea for hierarchy - based method is that creating and maintaining a tree of clusters and sub - clusters according to some kind of criterion to measure the distance of clusters , the procedure will be sloped until some terminal conditions are satisfied . hierarchical clustering method can be further classified into agglomerative and divisive hierarchical clustering , depending on whether the hierarchical decomposition is formed in a bottom - up or top - down fashion . most hierarchical clustering methods can produce the better results when the clusters are compact or spherical in shape . but they do not perform well if the clusters are any shape or there are outliers . a main reason is that the most hierarchical clustering methods employ medoid - based measurement as distance between clusters 基于層次方法的聚類的基本思想足:根據給定的簇間距離度量準則,構造利維護一棵由簇利子簇形成的聚類樹,直至滿足某個終結條件為止。根據層次分解是自底向上還是自頂向下形成,層次聚類方法可以分為凝聚的( agglomerative )和分裂的( divisive ) 。人多數層次聚類算法在緊密簇或球形簇結構下能夠產生較好的聚類效果。