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Exercise

Defining the forecasting pipeline

Now you'll define the forecasting model and parameters for the MLForecast pipeline. This step prepares the model configuration that will be used for time series forecasting in the pipeline.

Instructions

100 XP
  • Import LGBMRegressor from lightgbm.
  • Instantiate a LGBMRegressor model with 100 estimators and a learning rate of 0.05.
  • Create a dictionary named params that includes the frequency ("h"), lags (1-24), and date features ("month", "day", "dayofweek", "week", and "hour").