[R] Hierarchical clustering using own distance matrices
Newbie@R
ayesha.2.jadoon at googlemail.com
Tue May 25 23:12:06 CEST 2010
Hey Everyone!
I wanted to carry out Hierarchical clustering using distance matrices i have
calculated ( instead of euclidean distance etc.)
I understand as.dist is the function for this, but the distances in the
dendrogram i got by using the following script(1) were not the distances
defined in my distance matrices.
script:
var<-read.table("the distance matrix i calculated", header=TRUE, sep=" ")
var_HC<-hclust(as.dist(var),method="average")
var_dendro<-as.dendrogram(var_HC)
plot(var_dendro,ylim=c(0,5), nodePar =list(lab.cex = 0.3), header=title(" My
Distance Matrix"))
I did some research and found that the hclust function (from the hclust help
page):
"...Initially, each object is assigned to its own cluster and then the
algorithm proceeds iteratively, at each stage joining the two most similar
clusters, continuing until there is just a single cluster. At each stage
distances between clusters are recomputed by the Lance–Williams
dissimilarity update formula according to the particular clustering method
being used. ..."
I am wondering is there another function that doesnt do " At each stage
distances between clusters are recomputed by the Lance–Williams
dissimilarity update formula according to the particular clustering method
being used.."???
I hope my message was clear, any help would be greatly appreciated.
Thanks!!
A.Jadoon
Kings College London
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