Hierarchical method : create a hierarchical decomposition of the set of data objects . 層次的方法:對給定數(shù)據(jù)對象集合進(jìn)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(jù)給定的簇間距離度量準(zhǔn)則,構(gòu)造利維護(hù)一棵由簇利子簇形成的聚類樹,直至滿足某個終結(jié)條件為止。根據(jù)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(shù)層次聚類算法在緊密簇或球形簇結(jié)構(gòu)下能夠產(chǎn)生較好的聚類效果。