# How to interpret the PAM output

I am using the PAM function in R, and I don't understand how to evaluate its output. Whereas in K-means the ratio between the between sum of squares to the total sum of squares already gives a very good insight into the outcome of the function, PAM has no such measure in its output. How can I assess if the model is good or bad?

You may look at the silhouette plot

library(cluster)

## generate 25 objects, divided into 2 clusters.
x <- rbind(cbind(rnorm(10,0,0.5), rnorm(10,0,0.5)),
cbind(rnorm(15,5,0.5), rnorm(15,5,0.5)))
pamx <- pam(x, 2)

spam <- silhouette(pamx)
plot(spam)


You can get one value using:

mean(spam[,3])


Giving 0.880. (The value is between -1 to 1. While 1 means perfect clusters, and the lower it gets the less good the clusters are)

• This is precisely what I was looking for! It's a bit late for my master thesis, but it will be handy in the upcoming article! Thanks! – ccoutinho Feb 8 '16 at 9:05