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| Vendor: | Pegasystems |
|---|---|
| Exam Code: | PEGACPDS88V1 |
| Exam Name: | Certified Pega Data Scientist 8.8 |
| Exam Questions: | 140 |
| Last Updated: | October 5, 2026 |
| Related Certifications: | Pega Certified Data Scientist |
| Exam Tags: | Data Scientist |
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Which two factors do you inspect to access the general health of the adaptive models in Prediction Studio? (Choose Two)
These factors indicate how accurate and explainable the models are, which are key measures of model health. The number of responses and decisions are related more to model usage rather than health.
The management team at U+ Insurance wants to improve the experience of dissatisfied customers. The customers send the feedback through email.
To detect the sentiment of the incoming emails, which type of prediction do you need to configure in Prediction Studio?
To detect the sentiment of the incoming emails, you need to configure atext analytics prediction1234in Prediction Studio. A text analytics prediction is a type of prediction that uses natural language processing (NLP) to analyze text data and extract insights, such as topics, entities, and sentiments. You can use a text analytics prediction to detect the sentiment of an email based on its content and assign a score ranging from -1 (negative) to 1 (positive). This can help you improve the customer experience by identifying dissatisfied customers and taking appropriate actions.
A best practice in data science is to use a control group. What business metric is supported by this practice?
The lift that the prediction generates Reference:
Using a control group is a best practice in data science that supports the business metric ofthe lift that the prediction generates.
When building a model using Pega machine learning, the validation hold-out set is used to____________and to____________. (Choose Two)
When building a model using Pega machine learning, the validation hold-out set is used totrain the modelsand tocheck for robustness of candidate models.
Which decision component allows you to monitor the real-time performance of a third- party Churn Model?
A scorecard model is a type of predictive model that allows you to monitor the real-time performance of a third-party churn model. A scorecard model compares the predicted churn probability with the actual churn outcome and calculates a performance score for each customer segment. Reference: https://academy.pega.com/module/predictive-analytics/topic/using-scorecard-models
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