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I have hourly electricity consumption data for each building and I want to forecast the next 7 days (hourly) every Monday. When I feed data to the model each Monday, the model should retain past data or parameters so that it improves in accuracy over time.
I mean model should remember past data or parameters to improve accuracy iteratively.
how can i achieve it?
The text was updated successfully, but these errors were encountered:
@AvinashUtekar so typically what one does is to feed updated context to the model, i.e. next week, feed the ground-truth of the past week etc. and this way one can get the forecast based on the most recent ground-truth...
I have hourly electricity consumption data for each building and I want to forecast the next 7 days (hourly) every Monday. When I feed data to the model each Monday, the model should retain past data or parameters so that it improves in accuracy over time.
I mean model should remember past data or parameters to improve accuracy iteratively.
how can i achieve it?
The text was updated successfully, but these errors were encountered: