I have a collection of data for a multiplayer game (2000 games, 10 players each). I would like to create clusters from this data, each containing the ids of 3 players that had played against each other. For example, assume player A played against player B, B played against C, and C played against A. I'm trying to figure out a way to detect A,B, and C from the data. I was thinking of using kmeans but this may not work as i do not know the number of clusters. Please help
closed as unclear what you're asking by Michael Chernick, kjetil b halvorsen, Firebug, Sean Easter, SmallChess Apr 11 '17 at 12:28
Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.
You appear to be looking for 3-Cliques, not for clusters.
Unless you are also looking for larger cliques, you likely won't find an "algorithm" for this, because it is straightforward.
For any node A: For any neighbors B < C of A: If A < B and B and C are connected: report ABC as 3-clique
Clustering algorithms try to solve a different problem, so they won't be useful to you.