Create a model-level explainability module and import action

These prerequisites should be in place:

• Your model must have historic and related data export actions defined. 
• You must run a data collection successfully.
• Data for this module depends on a forecast model trained with Amazon Ensemble.

To create a model-level explainability module and import action:

1. Create a list called "Forecast Models."
2. In Pivot view:
   • Place Forecast Feature Names as Rows dimensions.
   • Place Line Items as the Column dimension and remove Time.
   • Place the Forecast Models in the Pages dimension (see screenshot 1 below).
   • Select OK.

3. Add a line item called Feature Contribution.
4. In Blueprint view, select None in the Summary column for the Feature Contribution line item.

5. From the regular view:
   • Select Import from the Data dropdown.
6. From the Select Source dialog:
   • Select import_action_setup_model_explainability.csv.
   • Click the Select button.
7. From the File Options dialog:
   • Use the Set Default File dropdown to select Admins Only.
   • Select Next.
8. From the Import dialog, Mapping tab:
   • Map Source to Target. The table below provides an example. Your sources and targets will vary.

• Select Only update imported cells on the right (see screenshot 2 below).
• Note: You don't need to map within the Forecast Feature name tabs. The Forecast Feature name tab will have no Target items until you run a Forecast action.
• From the Forecast Explainability Line Items tab:

• Select Run Import.
  This is how you define the import to the explainability module.
• Optional: from Import actions, rename import_action_setup_explainability to IMP Module Forecast Explainability.

Blueprint setup example:

9. Select OK.
Your explainability module is now ready. The next step is to import your model-level explainability.