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NEW QUESTION # 73
When you build a decision strategy, what property do you use to access the output of a prediction that is driven by a predictive model markup language (PMML) model?
- A. pxSegment
- B. pxResult
- C. nxOutcome
- D. pxEvidence
Answer: B
Explanation:
Explanation
The pxResult property is used to access the output of a prediction that is driven by a PMML model. It contains the predicted value or class for each record in the input data set. References:
https://academy.pega.com/module/predictive-analytics/topic/using-pmml-models
NEW QUESTION # 74
When building a predictive model, the use of testing and validation samples_______________
- A. increases the accuracy of models
- B. is mandatory for segmentation
- C. validates the quality of input data
- D. enables model validation in strategies
Answer: A
Explanation:
Explanation
The use of testing and validation samples increases the accuracy of predictive models by allowing you to evaluate how well they perform on unseen data and avoid overfitting or underfitting problems. References:
https://academy.pega.com/module/predictive-analytics/topic/creating-predictive-models
NEW QUESTION # 75
The Pega Customer Decision Hub delivers Next-Best-Actions consistently through multiple channels. To which of the following channels does this apply?
- A. Traditional newspaper
- B. Mobile
- C. Cable television
- D. Billboard
Answer: B
Explanation:
Explanation
The Pega Customer Decision Hub delivers Next-Best-Actions consistently through multiple channels. This applies to Mobile channels.
NEW QUESTION # 76
U+ Bank introduces a new credit card that has no historical customer behavior data. U+ Bank wants to offer this credit card on the personalized web portal. Given the scenario, which rule type must you use?
- A. Decision table
- B. When rule
- C. Pega machine learning model
- D. Adaptive model
Answer: D
Explanation:
Explanation
Given the scenario where U+ Bank introduces a new credit card that has no historical customer behavior data and wants to offer this credit card on the personalized web portal, you must use an adaptive model.
NEW QUESTION # 77
The standardized model operations process (MLOps) lets you replace a low-performing predictive model that drives a prediction with a superior one.
When you place the new model in shadow mode in the production environment, the current model___________
- A. drives the prediction
- B. no longer drives the prediction
- C. is automatically replaced
- D. uses the outcomes of the new model as predictors
Answer: A
Explanation:
Explanation
When you place the new model in shadow mode in the production environment, the current model still drives the prediction, but the new model runs in parallel and collects performance data for comparison. References:
https://academy.pega.com/module/predictive-analytics/topic/mlops
NEW QUESTION # 78
U+ Insurance uses Pega Process AI to route complex claims to an expert. As a data scientist, you have used the wizard to create a prediction with Case completion as the outcome to help with decision routing. You are tasked with monitoring the adaptive models. When you open the monitoring tab of the adaptive model rule, you see the following chart:
In this scenario, the system creates an adaptive model for each
- A. case type instance
- B. case type step
- C. case type
- D. case type stage
Answer: C
Explanation:
Explanation
In this scenario, the system creates an adaptive model for each case type, such as claim or complaint. The adaptive model learns from the outcomes of each case type and predicts the probability of case completion for each customer. References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m
NEW QUESTION # 79
The likelihood that an action will be accepted by the customer is stored in the Strategy property called_______
- A. pyBehavior
- B. pyLikelihood
- C. pyPropensity
- D. pyProbability
Answer: C
Explanation:
Explanation
The pyPropensity property stores the likelihood that an action will be accepted by the customer. It is calculated by a predictive model or an adaptive model and used in decision strategies to prioritize actions. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/using-predictio
NEW QUESTION # 80
When implementing a Next-Best-Action project, which step is recommended to be taken first?
- A. Define propositions
- B. Define prioritization formula
- C. Define business rules
- D. Define Issue and Group hierarchy
Answer: D
Explanation:
Explanation
When implementing a Next-Best-Action project, the recommended first step is to define Issue and Group hierarchy, which are used to organize and categorize propositions based on business objectives and customer needs. This step helps to align the project with the business vision and goals. References:
https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer
NEW QUESTION # 81
As a data scientist, you are tasked with configuring two predictions that are driven by an adaptive model: one for an inbound channel and one for an outbound channel. To which setting do you need to pay extra attention?
- A. Response timeout
- B. Control group
- C. Adaptive model
- D. Predictor fields
Answer: C
Explanation:
Explanation
As a data scientist, if you are tasked with configuring two predictions that are driven by an adaptive model, you need to pay extra attention to adaptive model settings.
NEW QUESTION # 82
As a data scientist, you are tasked with creating a new prediction that estimates a customers' likelihood to leave the business in the near future. The NBA analyst wants to move forward and use the prediction in Pega Customer Decision Hub to test the application. To unblock the NBA specialist, which task do you prioritize?
- A. Create the predictive model that drives the prediction
- B. Create the customer data model
- C. Create a placeholder scorecard to drive the prediction
- D. Create the prediction
Answer: A
Explanation:
Explanation
To unblock the NBA specialist, as a data scientist, you should prioritize creating the predictive model that drives the prediction.
NEW QUESTION # 83
The implementation of Next-Best-Action must involve
- A. defining business issue and group hierarchy
- B. inclusion of third party predictive models
- C. defining a prioritization formula using contact policies
- D. building a product catalog
Answer: A
Explanation:
Explanation
The implementation of Next-Best-Action must involve defining business issue and group hierarchy, which are used to organize and categorize propositions based on business objectives and customer needs. References:
https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer
NEW QUESTION # 84
The standardized machine learning process (MLOps) lets you replace a low-performing predictive model that drives a prediction with an updated model. When you approve the model, a change request is automatically generated in__________
- A. an external environment
- B. the production environment
- C. the business operations environment
Answer: B
Explanation:
Explanation
When you approve the updated model in the standardized machine learning process (MLOps), a change request is automatically generated in the production environment.
NEW QUESTION # 85
Adaptive models can start to learn without historical evidence. What is the starting propensity of every action?
- A. 0
- B. 0.5
- C. 1
- D. 2
Answer: B
Explanation:
Explanation
Adaptive models can start to learn without historical evidence. The starting propensity of every action is 0.5.
NEW QUESTION # 86
In a decision strategy, to remove propositions based on the current month, you use a
- A. Data Strategy property
- B. Filter component
- C. Calendar component
- D. Calendar strategy property
Answer: C
Explanation:
Explanation
The calendar component is used to remove propositions based on the current month, day of week, or time of day. It can also be used to apply seasonal adjustments to propositions. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/using-calendar-
NEW QUESTION # 87
When building a model using Pega machine learning, the validation hold-out set is used to____________and to____________. (Choose Two)
- A. select the best model
- B. train the models_____________________
- C. check for robustness of candidate models
- D. analyze the performance characteristics of candidate models
- E. compare their performance
Answer: B,C
Explanation:
Explanation
When building a model using Pega machine learning, the validation hold-out set is used to train the models and to check for robustness of candidate models.
NEW QUESTION # 88
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