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Exercise

Forecasting with ML Models

As a data science consultant, your task is to predict US hourly electricity demand. In the previous task, you cleaned and prepared the data. Now, it's time to use machine learning models to build your forecast.

We previously covered the statsforecast workflow, and now you'll apply the same principles using mlforecast.

The train and test datasets, as well as models (LGBMRegressor(), XGBRegressor(), LinearRegression()), are preloaded.

The MLForecast class has been imported from the mlforecast package, ready to use. Let's build your forecast!

Instructions 1/2

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  • Define the ML models using LGBMRegressor(), XGBRegressor(), and LinearRegression().
  • Set up the MLForecast object and set the frequency to hourly ('h').