构造数据：

> dataset = matrix(c(1,2,+ 1.2,2,+ 8,9,+ 0.9,1.8,+ 7,10,+ 8.8,9.2), nrow=6, byrow=T)> dataset     [,1] [,2][1,]  1.0  2.0[2,]  1.2  2.0[3,]  8.0  9.0[4,]  0.9  1.8[5,]  7.0 10.0[6,]  8.8  9.2

聚类：

> d = dist(dataset)> d           1          2          3          4          52  0.2000000                                            3  9.8994949  9.7590983                                 4  0.2236068  0.3605551 10.1118742                      5 10.0000000  9.8812955  1.4142136 10.2200783           6 10.6150836 10.4690019  0.8246211 10.8245092  1.9697716> hclust(d, method = "complete")Call:hclust(d = d, method = "complete")Cluster method   : complete Distance         : euclidean Number of objects: 6 > hc = hclust(d, method = "complete")> plot(hc)

分成两个簇：

> democut<-cutree(hc,k=2)> democut[1] 1 1 2 1 2 2

参考：

http://www.r-tutor.com/gpu-computing/clustering/hierarchical-cluster-analysis

http://stat.ethz.ch/R-manual/R-devel/library/stats/html/hclust.html http://ecology.msu.montana.edu/labdsv/R/labs/lab13/lab13.html