The Regression model zone is where the Advanced Forecast is created. More complete details about these steps are available [here](article:38).

![Screenshot 2023-01-13 at 16.07.24.png](kS2GdVCMT23a)

The [split recipe](recipe:split_historical_ts_data_forecasted) separates the [input dataset](dataset:historical_ts_data_forecasted) into a [train](dataset:historical_ts_data_train) and a [test](dataset:historical_ts_data_test) dataset. 

The [regression model](saved_model:MZEeNBre) is trained and tested on the respective datasets and the model is evaluated on the [test](dataset:historical_ts_data_test) and a [train](dataset:historical_ts_data_train) set to collect test and in sample forecasts. These evaluation results stored in two distinct datasets serve as inputs to a [stack recipe](recipe:compute_rf_evaluation_results_stacked) to facilitate flow automation in the next zone. 

The [score recipe](recipe:score_to_forecast_data_forecasted_joined) is used to apply the regression model to the dataset containing the values to forecast ([to_forecast_data_forecasted](dataset:to_forecast_data_forecasted)) and generate the predicted values over the next horizons. 

