flexmeasures.data.models.forecasting.custom_models.lgbm_model

Classes

class flexmeasures.data.models.forecasting.custom_models.lgbm_model.CustomLGBM(max_forecast_horizon=48, probabilistic=True, models_params=None, auto_regressive=True, use_past_covariates=False, use_future_covariates=False, ensure_positive=False)

Multi-horizon forecasting model using LightGBM.

This class implements a forecasting model that utilizes LightGBM (LGBM) for multi-horizon forecasting. It inherits from BaseModel and is designed to forecast multiple horizons into the future based on the provided maximum forecast horizon.

Attributes:

max_forecast_horizon (int): The maximum number of hours into the future for forecasting. probabilistic (bool): Flag indicating whether the model is probabilistic. models (List): List to hold multiple LGBM models.

__init__(max_forecast_horizon=48, probabilistic=True, models_params=None, auto_regressive=True, use_past_covariates=False, use_future_covariates=False, ensure_positive=False)

_setup() → None

Set up the forecasting models.

Subclasses must implement this method to populate self.models. Typically, one model is created per forecast horizon (up to self.max_forecast_horizon). These models must provide fit() and predict() methods compatible with darts TimeSeries.