I have both numeric and binary data in my data set with 73 observations. I read a lot about which distance metric and which clustering technique to use especially from this web site. I decided to use Gower distance metrics and K-medoids. In R, I used package "cluster", and function "daisy" with metric="gower". So I got a 73*73 matrix. Now, as I understood, this is not a distance matrix, it is a similarity matrix that I am confused what to do after now. I use function pam: pam(x, k, diss = inherits(x, "dist")... Should I use the 73*73 matrix which I got from daisy function?
See the documentation of the
pam function, which implements K-medoids.
In case of a dissimilarity matrix,
xis typically the output of
and the documentation of
“Gower's distance” is chosen by metric
"gower"or automatically if some columns of x are not numeric. Also known as Gower's coefficient (1971), expressed as a dissimilarity, this implies that a particular standardisation will be applied to each variable, and the “distance” between two units is the sum of all the variable-specific distances, see the details section.
The documentation of R is pretty good... use it.