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I have the following dataset. For every time point (at a frequency of 1 hour), we can construct a graph consisting of 20 nodes representing countries. Each country (node) is characterized by 5 variables. The edges between countries are directed and weighted. Now, let's assume we have one year's worth of data, equating to 24*365 unique graphs. Each graph is associated with a label that we aim to predict. How would you approach such problem?

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  • $\begingroup$ A graph can be represented by a matrix. Each of your countries along the rows and columns, properties of each country can be represented as several vectors. So all in all you have a matrix+several vectors per each observation. That would be a faithful albeit, perhaps, non-optimal representation $\endgroup$
    – Cryo
    Commented May 9 at 20:55

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