On 28.03.2017 00:02, treinz wrote: > I think I'm confused by how the input and output are related to each other > in the layered model. Let's say each network in my data is 1 of the top 3 > layers of Fig. 1 of the paper you mentioned. I don't have a well-defined > sequence variable for the networks except that I know they're related to > each other but not exactly the same. You can think of them as realizations > of different perturbed states of the same underlying network but each comes > with some experimental noise. I'm expecting the algorithm to tell me how > many of these perturbed states are there in my data and what's the SBM for > each of these states. I'm thinking maybe the layered SBM can help me with > that. But it seems that in order to use the layered model, I have to first > collapse all the networks, which I think will lose a lot of information in > my data and I don't know how to interpret the output.
I don't really understand what you want, exactly, and what you mean by "perturbed states". Forget about the layered SBM for a moment, and try to explain clearly and succinctly how your data is, and what you want to obtain in the end. Best, Tiago -- Tiago de Paula Peixoto <[email protected]>
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