[ACCEPTED]-Clustering list for hclust function-hclust
Accepted answer
I will use the dataset available in R to 8 demonstrate how to cut a tree into desired 7 number of pieces. Result is a table.
Construct 6 a hclust object.
hc <- hclust(dist(USArrests), "ave")
#plot(hc)
You can now cut the tree 5 into as many branches as you want. For my 4 next trick, I will split the tree into two 3 groups. You set the number of cuts with 2 the k parameter. See ?cutree and the use of paramter 1 h which may be more useful to you (see cutree(hc, k = 2) == cutree(hc, h = 110)).
cutree(hc, k = 2)
Alabama Alaska Arizona Arkansas California
1 1 1 2 1
Colorado Connecticut Delaware Florida Georgia
2 2 1 1 2
Hawaii Idaho Illinois Indiana Iowa
2 2 1 2 2
Kansas Kentucky Louisiana Maine Maryland
2 2 1 2 1
Massachusetts Michigan Minnesota Mississippi Missouri
2 1 2 1 2
Montana Nebraska Nevada New Hampshire New Jersey
2 2 1 2 2
New Mexico New York North Carolina North Dakota Ohio
1 1 1 2 2
Oklahoma Oregon Pennsylvania Rhode Island South Carolina
2 2 2 2 1
South Dakota Tennessee Texas Utah Vermont
2 2 2 2 2
Virginia Washington West Virginia Wisconsin Wyoming
2 2 2 2 2
lets say,
y<-dist(x)
clust<-hclust(y)
groups<-cutree(clust, k=3)
x<-cbind(x,groups)
now you will get for each record, the 2 cluster group. You can subset the dataset 1 as well:
x1<- subset(x, groups==1)
x2<- subset(x, groups==2)
x3<- subset(x, groups==3)
Source:
stackoverflow.com
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