Hi Tiago,
On 3 Jul 2020, at 19:05, Tiago de Paula Peixoto <tiago@skewed.de> wrote:
Hi Davide,
Am 03.07.20 um 11:31 schrieb Davide Cittaro:
Hello, I'm testing the new Planted Partition model in graph-tool on my data, indeed I'm finding interesting results. I have some questions/observations, though. - PPBlockState returns a relatively large number of partitions on large networks, which is fine and expected. When I use NSBM, instead, I make use of the hierarchy not only because I can "abstract" partitions up to a certain level, but also because the hierarchy has a meaning in my case. Is there (or will it be there) a hierarchical formulation of the PPBlockState?
A hierarchical prior for the PP model is certainly feasible, and it is something that could come up in the future, but I can't promise when.
Would it make sense to get a graph from partitions (where edges are weighted on connectivity among them) and apply NSBM then? This would produce a mixed model where the deepest level is actually a PP, and the hierarchy doesn't assume any constraint on assortativity.
- As far as I understand, if the assortativity is the dominant pattern the difference between PP and NSBM is negligible. I don't know how to quantify "negligible" as the differences in entropies are at least in the order of 1e2 in the cases I tested (seems pretty large to me); I would be happy to switch to PP, also given the shorter runtime so far, but I'm a bit concerned about these differences.
I do not recommend simply switching to PP for every analysis. As was described in the paper, the SBM is still a more powerful model, that is capable of better capturing the network structure in a wider variety of cases.
You are so right. I have some datasets in which PP doesn't seem to perform as well as NSBM.
To answer your question, you can test whether the two models give similar answers by comparing their partitions. You can use the partition_overlap() function for that.
Ok, thanks. Another function I didn't know. Best, d