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  1. Home
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  3. PEGACPDS88V1

Pegasystems PEGACPDS88V1 Exam (page: 1)
Pegasystems Certified Pega Data Scientist 8.8
Updated on: 11-Nov-2025

Viewing Page 1 of 29
PEGACPDS88V1 PDF 140 Questions

To enable an assessment of its reliability the adaptive model produces four outputs:
propensity,performance, evidence and positives.
The Performance of an adaptive model that has not collected any evidence yet is______.

  1. 75
  2. 0
  3. 50
  4. 100

Answer(s): C

Explanation:

The performance of an adaptive model that has not collected any evidence yet is 50. This means that the model is not confident about its predictions and assigns equal probability to all actions.


Reference:

https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule- /rule-decision-/rule-decision-adaptivemodel/main.htm



When you create a decision strategy from scratch and want to associate an adaptive model with each action, you need to_______.

  1. Capture the customer's response
  2. Define the adaptive model instances in Adaptive Decision Manager
  3. Link all actions with an adaptive model decision component
  4. Create an adaptive model rule for each action

Answer(s): B

Explanation:

To associate an adaptive model with each action in a decision strategy created from scratch, you must define the adaptive model instances in the Adaptive Decision Manager.



What are two of the results of an adaptive model? (choose two)

  1. Performance
  2. Evidence
  3. Priority
  4. Segment

Answer(s): A,B

Explanation:

Performance and evidence are two of the results of an adaptive model. Performance is the percentage of positive responses that the model predicts for a given predictor profile. Evidence is the number of customers who exhibited statistically similar behavior.


Reference:

https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule- decision-/rule-decision-adaptivemodel/main.htm



The adaptive model component in a decision strategy computes

  1. A single propensity value for all actions
  2. A unique accept rate for each action
  3. A single accept rate for all actions
  4. A propensity value for each action

Answer(s): D

Explanation:

The adaptive model component in a decision strategy computes a propensity value for each action. Propensity is the likelihood of a positive response for a given action and predictor profile. It ranges from 0 to 100.


Reference:

https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule- decision-/rule-decision-adaptivemodel/main.htm



An adaptive adaptive model component in a decision: propensity, performance, evidence, and positives.
What is evidence in the context of an adaptive model?

  1. The likelihood of a statistically similar behavior
  2. The number of customers who exhibited statistically similar behavior
  3. The number of statistical bins that arc generated by the system
  4. The number of outcomes that system registered

Answer(s): B

Explanation:

Evidence is the number of customers who exhibited statistically similar behavior. It indicates how much data the model has collected for a given predictor profile. The higher the evidence, the more reliable the model is.


Reference:

https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule- decision-/rule-decision-adaptivemodel/main.htm



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