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Free PEGACPDS88V1 Exam Braindumps (page: 3)

Page 3 of 36
PDF with 140 Questions

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



Which adaptive model output is automatically mapped to a strategy property?

  1. Performance
  2. Score
  3. Propensity
  4. Evidence

Answer(s): C

Explanation:

Propensity is the adaptive model output that is automatically mapped to a strategy property. 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



When selecting the list of predictors for an adaptive model you should

  1. Select up to a maximum of 500 predictors
  2. Consider properties from a wide range of sources
  3. Always use numeric type for integer properties
  4. Select at least one date property

Answer(s): B

Explanation:

When selecting the list of predictors for an adaptive model you should consider properties from a wide range of sources. Predictors are properties that influence the customer behavior and can be derived from various sources such as customer profile, interaction history, proposition details, etc.


Reference:

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



What happens when you increase the performance threshold setting of an adaptive model rule?

  1. The number of active predictors increases
  2. The performance of the model is increased
  3. The correlation threshold decreases
  4. The number of active predictors may decrease

Answer(s): D

Explanation:

When you increase the performance threshold setting of an adaptive model rule, the number of active predictors may decrease. The performance threshold is the minimum performance that a predictor must have to be included in the model. If you increase this value, some predictors may not meet the criteria and be excluded from the model.


Reference:

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






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