Hierarchical Cluster 層次聚類
阿新 • • 發佈：2019-01-04
構造資料：
?| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 |
>
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
|
聚類：
?| 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 |
>
d = dist(dataset)
>
d
1
2 3 4 5
2
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)
|
分成兩個簇：
?| 1 2 3 |
>
democut<-cutree(hc,k=2)>
democut
[1]
1 1 2 1 2 2
|
參考：
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