OK. Fig 1 and its legend in this paper (http://ieeexplore.ieee.org/document/7442167/) is a summary of what I just stated before.
-Tim
At 2017-03-28 07:18:52, "Tiago de Paula Peixoto" tiago@skewed.de wrote:
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 tiago@skewed.de