[Update 1] Louvain-Performance and Self-Loops
For background, please see my earlier post. Recall that we sometimes want the presence of self-loops to be stronger than inter-community links. That is, despite the weight of some inter-community edge (e_1, e_2), the presence of heavy self-loops (e_1, e_1) and (e_2,…
Louvain-Performance and Self-Loops
In phase 2 of each pass, the Louvain algorithm creates a collapsed version G’ of the current clustering G. Nodes in a community C in G are represented as a single vertex V_c in G’. Information about the weights of…
[Update 1] Louvain-Performance: Weights of Nonexistent Edges
Earlier, I wrote a post on how performance on weighted graphs uses a meaningful maximum M to account for the weights of nonexistent edges. At that time, my challenges were (1) figuring out how to calculate M, and (2) changing my…
Louvain-Performance: Weights of Nonexistent Edges
One of the tricky things about calculating performance is that it factors in nonexistent edges between vertices in different communities. The more of these edges exist, the higher the overall performance score, because they count as correctly-interpreted edges. That is, since the two…