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1. What is the primary purpose of the Context Dictionary?

2. How often does the adaptive model update its learning?

3. What does the Customer Profile Viewer allow data scientists to do?

4. Which two elements must be mapped when setting up outcomes in a prediction? (Choose two)

5. Which parameters can be configured when creating an adaptive model? (Choose two)

6. Which Pega component is used to manage and test adaptive models?

7. How does exporting data support model governance?

8. What filtering option is available when exporting adaptive model data?

9. What does the term “training data” refer to in prediction models?

10. How can you validate the quality of a new prediction model?

11. When is a new model instance created in the adaptive model system?

12. Which action lifecycle stage is used to determine if a customer is eligible to receive an action?

13. What tool visualizes predictor performance across multiple adaptive models?

14. What part of exported data helps identify rare outcomes affecting learning?

15. Which of the following are considered model health indicators? (Choose two)

16. Where can you review inactive predictors in an adaptive model?

17. Which of the following may indicate model fatigue or bias? (Choose two)

18. 1.Which layer in the Customer Decision Hub governs arbitration between competing actions?

19. Which of the following can be used as a predictor in a prediction model? (Choose two)

20. Which two predictors would likely be considered as high-value for predicting product interest? (Choose two)

21. Which of the following are valid output types for Pega prediction models?

22. Which metric indicates the balance between precision and recall?

23. Which tool is used in Pega to initiate the export of adaptive model data?

24. Why should you review a confusion matrix for your prediction?

25. Why should predictors be normalized before use in an adaptive model?

26. What is the significance of model evidence?

27. How is lift used in evaluating a prediction?

28. What can trigger adaptive model retraining in Pega?

29. What is the best way to reuse business logic across multiple strategies?

30. What is the primary reason to export adaptive model data?

31. How can you interpret a model with low performance but high evidence?

32. Which of the following can be used as outcomes in an adaptive model? (Choose two)

33. Which two types of rules are used to configure engagement policies in Customer Decision Hub? (Choose two)

34. Which Pega component is responsible for providing adaptive learning models in the Customer Decision Hub?

35. What information does the Next-Best-Action Designer capture? (Choose two)

36. Which two types of users typically analyze exported adaptive model data? (Choose two)

37. What defines how the actions are grouped within the NBA Designer?

38. Which model outputs are generated by an adaptive model rule? (Choose two)

39. Which component helps visualize how actions move through the decision strategy?

40. Which feature allows adaptive models to avoid overfitting during training?