Pegasystems PEGACPDS88V1 Exam
Certified Pega Data Scientist 8.8 (Page 4 )

Updated On: 7-Feb-2026

Adaptive model components can output__________

  1. An option___________
  2. An optimized strategy
  3. The number of customer's eligible for an action
  4. The customer's propensity to accept an action

Answer(s): D

Explanation:

Adaptive model components can output the customer's propensity to accept an 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 model instance is created when you________

  1. Execute a strategy containing the adaptive model component
  2. Open the Adaptive model management landing page
  3. Restart the Adaptive Decision Manager Service
  4. Save the Adaptive model rule

Answer(s): A

Explanation:

An adaptive model instance is created when you execute a strategy containing the adaptive model component. The adaptive model component references an adaptive model rule that defines the predictors and the outcome of the model. The adaptive model instance stores the data and the statistics of the model for a specific context and action.


Reference:

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



Which data is usually not appropriate to be used as a predictor?

  1. Customer zip code
  2. Historical interaction data
  3. Customer name
  4. Usage data

Answer(s): C

Explanation:

Customer name is usually not appropriate to be used as a predictor. A predictor is a property that influences the customer behavior and can be derived from various sources such as customer profile, interaction history, proposition details, etc. Customer name is not likely to have any impact on the customer's preferences or responses, and it may also violate privacy regulations.


Reference:

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



Which statement about predictive models is true?

  1. Predictive models need historical data to be created
  2. Predictive models need to be specified in a data attribute
  3. Predictive models are always associated with an action
  4. Predictive models need unstructured bie data

Answer(s): A

Explanation:

Predictive models need historical data to be created. Predictive models are statistical models that use historical data to learn patterns and trends and make predictions for future outcomes. Predictive models can be built with Pega machine learning or imported from third-party tools such as PMML or H2O.


Reference:

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



The use of an imported third-party model in a decision strategy is____

  1. Only possible after conversion into a Pega machine learning model
  2. Identical to the use of an adaptive model
  3. Similar to the use of a model built with Pega machine learning
  4. Only possible after conversion into Pega markup language

Answer(s): C

Explanation:

The use of an imported third-party model in a decision strategy is similar to the use of a model built with Pega machine learning. You can use a predictive model component in a decision strategy to reference an imported third-party model and pass the input parameters and receive the output score. You do not need to convert the third-party model into a Pega machine learning model or Pega markup language.


Reference:

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






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