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PEGACPDS88V1 Exam
Pega Certified Data Scientist
Questions & Answers
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Questions & Answers PDF Page 2 
 
Version: 4.1 
 
 
 
  Question: 1  
 
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 . 
 
A. 75 
B. 0 
C. 50 
D. 100 
 
 
   Answer: 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 
 
  Question: 2  
When you create a decision strategy from scratch and want to associate an adaptive model with each 
action, you need to . 
 
A. Capture the customer's response 
B. Define the adaptive model instances in Adaptive Decision Manager 
C. Link all actions with an adaptive model decision component 
D. Create an adaptive model rule for each action 
 
 
   Answer: 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. 
 
  Question: 3  
What are two of the results of an adaptive model? (choose two) 
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Questions & Answers PDF Page 3 
 
 
A. Performance 
B. Evidence 
C. Priority 
D. Segment 
 
 
   Answer: 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 
 
  Question: 4  
The adaptive model component in a decision strategy computes 
 
A. A single propensity value for all actions 
B. A unique accept rate for each action 
C. A single accept rate for all actions 
D. A propensity value for each action 
 
 
   Answer: 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 
 
  Question: 5  
An adaptive adaptive model component  in a decision: propensity, performance, evidence, and 
positives. 
What is evidence in the context of an adaptive model? 
 
A. The likelihood of a statistically similar behavior 
B. The number of customers who exhibited statistically similar behavior 
C. The number of statistical bins that arc generated by the system 
D. The number of outcomes that system registered 
 
 
   Answer: B  
Explanation: 
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Questions & Answers PDF Page 4 
 
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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