Hi,
I already have a dissimilarity matrix and I am submitting the results to
the elbow.obj method to get an optimal number of clusters. Am I reading
the below output correctly that I should have 17 clusters?
code:
top150 <- sampleset[1:150,]
{cluster1 <- daisy(top150
, metric = c("gower")
, stand = TRUE
, type = list(symm = 1))
}
dist.obj <- dist(cluster1)
hclust.obj <- hclust(dist.obj)
css.obj <- css.hclust(dist.obj,hclust.obj)
elbow.obj <- elbow.batch(css.obj)
[1] "A \"good\" k=17 (EV=0.80) is detected when the EV is no less than
0.8\nand the increment of EV is no more than 0.01 for a bigger k.\n"
attr(,"class")
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