Pegasystems PEGACPDS88V1 Certified Pega Data Scientist 8.8 Exam Practice Test

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Total 140 questions
Question 1

The result of a Predictive Model is stored in a property called__________.



Answer : D


Question 2

As a data scientist, you are asked to create a prediction to optimize the click-through rate of a web banner. What type of prediction do you need to create in Prediction studio?



Answer : C

Customer Decision Hub Reference:

To optimize the click-through rate of a web banner, you need to create aCustomer Decision Hubprediction.


Question 3

When defining outcomes for an Adaptive Model you must define



Answer : C

When defining outcomes for an adaptive model, you must define one or more positive behavior values, which indicate that the customer accepted or responded to the offer. You can also define negative and neutral behavior values, but they are optional. Reference: https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/configuring-adaptive-models


Question 4

Which value is output by an Adaptive Model?



Answer : C

The value that is output by an adaptive model is behavior, which indicates the likelihood that the customer will accept or respond to an offer. Behavior is also known as propensity or probability in decision strategies. Reference: https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/using-adaptive-models-decision


Question 5

As a data scientist, you want to use a predictive model to detect potential churn for a telecom company.

Which three options do you have? (Choose Three)



Answer : A, D, E

Import a third party PMML model1: PMML stands for Predictive Model Markup Language, which is an XML-based standard for representing predictive models. You can import a PMML model that was created by another tool or platform into Pega and use it in your strategies.

Create an adaptive self-learning model1: An adaptive model is a type of predictive model that learns from customer responses and adapts its predictions over time. You can create an adaptive model in Pega and configure its parameters, such as learning rate, decay rate, and performance goal.

Use Pega machine learning to build a model1: Pega machine learning is a feature that allows you to build predictive models using various algorithms, such as decision trees, logistic regression, neural networks, and random forests. You can use Pega machine learning to build a model from your data and evaluate its performance.


Question 6

When implementing a Next-Best-Action project, which step is recommended to be taken first?



Answer : A

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. Reference: https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer


Question 7

When building a predictive model, at what stage do you compare the performance of predictive models?



Answer : D

When building a predictive model, you compare the performance of predictive models at the Model Comparison stage. This stage allows you to select the best model based on various metrics, such as accuracy, lift, or area under curve (AUC). Reference: https://academy.pega.com/module/predictive-analytics/topic/comparing-predictive-models


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Total 140 questions