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Pegasystems Certified Pega Data Scientist 88V1 Sample Questions (Q20-Q25):

NEW QUESTION # 20
A company wants to simulate decisions that requires large amounts of data. However, the organisation's live data is inaccessible. Your advice is to use a Monte Carlo data set. The Monte Carlo method

  • A. makes the organization's live data accessible
  • B. combines external data sets into a larger data set
  • C. enables the company to generate random data for most of its application needs
  • D. generates data that the company can use as input for adaptive decisioning

Answer: D

Explanation:
Explanation
The Monte Carlo method enables the company to generate data that simulates customer behavior and can be used as input for adaptive decisioning. The generated data is based on predefined probabilities and distributions that reflect realistic scenarios. References:
https://academy.pega.com/module/demonstrating-adaptive-learning-archived/topic/creating-monte-carlo-data-set


NEW QUESTION # 21
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. Adaptive model
  • B. When rule
  • C. Pega machine learning model
  • D. Decision table

Answer: A

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 # 22
Which statement about predictive models is true?

  • A. Predictive models need unstructured bie data
  • B. Predictive models are always associated with an action
  • C. Predictive models need historical data to be created
  • D. Predictive models need to be specified in a data attribute

Answer: C

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


NEW QUESTION # 23
U+ Bank wants to offer a 10% discount for customers whose CLV value is higher than 400. Which strategy component should you use to meet the new requirement?

  • A. Prioritize
  • B. Filter
  • C. Group By
  • D. Set Property

Answer: B

Explanation:
Explanation
To offer a 10% discount for customers whose CLV value is higher than 400, you should use the Filter strategy component.


NEW QUESTION # 24
.Prediction Studio supports keyword-based topic detection, model-based topic detection, or a combination of both. When using a text prediction based on machine learning with keywords configured,_________________.

  • A. keywords and training data have a similar impact on the model
  • B. the Must keywords are required to detect the topic
  • C. the keywords are ignored
  • D. the Not keywords function as negative features

Answer: D

Explanation:
Explanation
When using a text prediction based on machine learning with keywords configured, the Not keywords function as negative features, meaning that they reduce the probability of detecting the topic if they appear in the text. The Must keywords and May keywords do not have any impact on the machine learning model.
References: https://academy.pega.com/module/text-analytics/topic/configuring-keywords


NEW QUESTION # 25
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