[graph-tool] Questions about PPBlockState

Davide Cittaro cittaro.davide at gmail.com
Fri Jul 3 20:17:37 CEST 2020


Hi Tiago, 

> On 3 Jul 2020, at 19:05, Tiago de Paula Peixoto <tiago at 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


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