features

Description

This function identifies the columns to be used by the model for the forecasting task. Features can be selecte from among the columns defined in the cols_type and those generated in the calculated_cols section. Excluded from selection are the column_to_predict and any columns derived directly from it, to avoid data leakage and ensure model integrity. This feature selection is crucial, as it focuses the model's learning on relevant predictors while excluding the target variable and its derivatives. To guarantee a robust model, at least one subcategory of features must be included, ensuring the set of features is comprehensive and not empty.

Steps impacted

training

Example

features:
    categorical_columns:
        - pos_country
        - sku_category
    numerical_columns:
        - sku_price_perma