The implementation of Next-Best-Action must involve
Answer(s): B
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.
https://academy.pega.com/module/one-one-customer-engagement/topic/next- best-action-designer
Which component(s) do you use to calculate the average margin of four actions?
Answer(s): A
You can use one Set Property component to calculate the average margin of four actions by using an expression that sums up the margin values of each action and divides by four. You can then use this property in other components, such as Filter or Prioritize.
https://academy.pega.com/module/creating-and-understanding-decision-strategies- archived/topic/setting-properties
When building a predictive model, what is a valid predictor data type?
When building a predictive model, a valid predictor data type is Boolean, which can have only two values: true or false. Other valid predictor data types are numeric, date, and symbolic (categorical).
https://academy.pega.com/module/predictive-analytics/topic/predictor-data-types
Which two factors do you inspect to assess the general health of the adaptive models in Prediction Studio? (Choose Two)
Answer(s): C,D
To assess the general health of the adaptive models in Prediction Studio, you can inspect the performance of the models and the number of decisions. The performance of the models shows how well they predict customer behavior over time. The number of decisions shows how much data is available for each model to learn from.
https://academy.pega.com/module/predicting- customer-behavior-using-real-time-data-archived/topic/monitoring-adaptive-models
To enable an assessment of its reliability, the Adaptive Model produces three outputs: Propensity, Performance and Evidence. The performance of an Adaptive Model that has not collected any evidence is_________.
Answer(s): C
When an adaptive model has not collected any evidence, its performance is 0.5, which means that it has no predictive power and is equivalent to a random guess. As more evidence is collected, the performance can increase or decrease depending on how well the model predicts customer behavior.
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data- archived/topic/adaptive-models-overview
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