# Tag Info

2

I do not know how ClusteringComponents's PAM is implemented, but I strongly suspect that what you observe is an effect of the stopping criteria of the PAM algorithm. E.g. using cluster samples to compute the Silhouette measure might produce these kind of results.

3

If you can build a classifier for your data, e.g. $$F : \{p^k_1,p^k_2,...,p^k_{10}\} \longrightarrow P_i ,$$ then you can use the approach described in this discussion: "How can I determine the importance of variables from Classify?". Should I use some modification of PrincipalComponents or cluster analysis? The document Importance of variables ...

4

CommunityGraphPlot[g] will find community based on FindGraphCommunities[g] So that CommunityGraphPlot[g] is the same as CommunityGraphPlot[g, FindGraphCommunities[g]] You could put labels like the following to show # of members: n = 10; q = n*(n - 1)/2; g = CompleteGraph[n, EdgeWeight -> RandomReal[{0, 1}, {q}]]; com = ...

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