Why do i have faster runtime when using more frequent refits about skforecast HOT 2 CLOSED

Thank you so much for the explanation Javier!

It makes way more sense to me now :-)

I also see your point about the metric, thanks for the heads up!

from skforecast.

Hello @fredn19,

Thanks for opening the topic. You are right, normally you would expect less execution time for a smaller number of refits.

The reason why the time for refit=True was 2 min and for refit=7 was 30 min is parallelization. While refit=True allows parallelization, when refit is an integer other than 1, parallelization is not possible because the various model fits must follow a logical order. This configuration is automated thanks to n_jobs='auto'.

What I can suggest to reduce time when refit=7:

• Don't use interval forecasting for prototyping. It will speed up the backtesting process.
• If interval prediction is a must, reduce the number of n_boot. Probably a number around 200 will give you similar results.

By the way, you might be interested in reading this article about metrics when building a forecasting model:

https://towardsdatascience.com/forecast-kpi-rmse-mae-mape-bias-cdc5703d242d

Hope it helps!

Javier

from skforecast.