I'm creating time series forecasts for different geographies and wanted an expert opinion on how I can take into account geographic relationship to improve my model. Is there an algorithm that's suitable for this usecase? Let me know if you need more context

  • $\begingroup$ Please help me understand the use-case here. This is what I understood from your question; you are building a time-series forecasting model e.g. daily-temperature forecast for city A, B, and C; and you want to use geographic relationship. What does the geographic relationship implies? $\endgroup$
    – DataFramed
    Jul 16 at 4:15
  • $\begingroup$ @DataFramed That's correct, the geographic relationship would implies that these regions are in close proximity and hence can have similar trends. Hope this helps! $\endgroup$
    – Aks
    Jul 16 at 18:16

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