I'm having trouble trying to figure out how to evaluate different set of forecast values using GoogleSQL.
I have a table as follows:
date | country | actual_revenue | forecast_rev_1 | forecast_rev_2 |
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x/x/xxxx ABC 134644.64 153557.44 103224.35
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.
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The table is partitioned by date and country, and consists of 60 days worth of actual revenue and forecast revenue from different forecast modelling configurations.
3 questions here:
Is calculating R-squared / Root Means Square Error (RMSE) the best way to evaluate model accuracy in SQL?
If Yes to #1, do I calculate the R-squared/ RMSE for each row, and take the average value of them?
Is there some sort of GoogleSQL functionality/better optimized ways of doing this?
Not quite sure about the best way on doing this as I'm not familiar with the statistics territory.
Appreciate any guidance here Thank you!