I am studying geographic solar radiation data obtained from satellite images. I would like to and use cluster analysis and make some correlation analysis by clusters, instead of by pixel - as some authors have done.
The kind of data is not much 'clusterable', so the main idea here is just to reduce dimensions. I would like to use the PAM algorithm and, to decide the number of clusters, for that I would like to verify how much loss of information would I lose by doing so. I thought in using information from the objective function (i.e. sum of dissimilarities from a point to the medoid of its cluster).
How could I find the explained variance using k-medoids or PAM? Or which would be a good metric to show how much information is lost (or kept) when clusterizing?