[Jan 09, 2024] Fully Updated Dumps PDF - Latest PEGACPDS88V1 Exam Questions and Answers

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The PEGACPDS88V1 exam is intended for data scientists, data analysts, and other professionals who work with data on a regular basis. It is an ideal certification for those who want to develop their skills in data science and machine learning using Pega's tools. PEGACPDS88V1 exam is designed to test your understanding of the key concepts and techniques used in data science, as well as your ability to apply them to real-world problems.

 

NEW QUESTION # 12
The purpose of regular inspection is to detect factors that negatively influence the performance of the adaptive models and the success rate of the actions. Which two issues should be discussed with the business? (Choose Two)

• A. Predictors that are never used
• B. Actions that have a low number of responses
• C. Actions that are offered so often that they dominate other actions
• D. Actions for which the model is not predictive
• E. Predictors with a low performance_________

Answer: C,E

Explanation:
Explanation
When performing regular inspection of adaptive models, two issues that should be discussed with the business are predictors with a low performance and actions that are offered so often that they dominate other actions.

NEW QUESTION # 13
When building a model using Pega machine learning, the validation hold-out set is used to____________and to____________. (Choose Two)

• A. analyze the performance characteristics of candidate models
• B. compare their performance
• C. select the best model
• D. check for robustness of candidate models
• E. train the models_____________________

Answer: D,E

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 # 14
A legal firm wants to use text analytics for easier and faster access to information to helo with compliance related issues. The legal firm needs a taxonomy of legal concepts.
What is a taxonomy?

• A. The output of an expert survey
• B. A list of valid categories
• C. A sentiment analysis model
• D. A list of business rules

Answer: B

Explanation:
Explanation
A taxonomy is a list of valid categories that can be used to classify text documents or entities. A taxonomy can be hierarchical or flat, depending on the level of detail required. References:
https://academy.pega.com/module/text-analytics/topic/creating-taxonomy

NEW QUESTION # 15
An adaptive model instance is created when you________

• A. Execute a strategy containing the adaptive model component
• B. Open the Adaptive model management landing page
• C. Restart the Adaptive Decision Manager Service
• D. Save the Adaptive model rule

Answer: A

Explanation:
Explanation
An adaptive model instance is created when you execute a strategy containing the adaptive model component.
The adaptive model component references an adaptive model rule that defines the predictors and the outcome of the model. The adaptive model instance stores the data and the statistics of the model for a specific context and action. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision

NEW QUESTION # 16
Evidence an assessment of its viability, the Adaptive Model produces three outputs: Propensity, Performance and what is evidence in the context of an Adaptive Model? Performance and what is evidence in the context of an Adaptive Model?

• A. The likelihood of a statistically similar behavior
• B. The number of statistical bins used to evaluate the response
• C. The number of customers who exhibited statistically similar behavior
• D. The number of customers who have responded to the modeled offer

Answer: C

Explanation:
Explanation
Evidence is the number of customers who exhibited statistically similar behavior to the current customer and responded to the modeled offer. It indicates how reliable the propensity score is based on the available data.
References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m

NEW QUESTION # 17
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. Filter
• B. Group By
• C. Set Property
• D. Prioritize

Answer: A

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 # 18
U+ Insurance wants to use Pega Process Al to detect fraud and assign suspicious claims to a fraud expert for closer inspection.
To meet this requirement, how does an application developer use the outcome of a predictive fraud model in the case type that processes the incoming claim?

• A. Use the model outcome in the condition of a decision step.
• B. Use the prediction outcome in the condition of an assignment step.
• C. Use the model outcome in the condition of an assignment step.
• D. Use the prediction outcome in the condition of a decision step.

Answer: A

Explanation:
Explanation
Pega Process AI lets you bring your own predictive models to Pega and use predictions in case types to optimize the way your application processes work and meet your business goals.
To use the outcome of a predictive fraud model in the case type that processes the incoming claim, you need to use the model outcome in the condition of a decision step . This way, you can route suspicious claims to a fraud expert for closer inspection based on the model's prediction.

NEW QUESTION # 19
What are two of the results of an adaptive model? (choose two)

• A. Performance
• B. Evidence
• C. Priority
• D. Segment

Answer: A,B

Explanation:
Explanation
Performance and evidence are two of the results of an adaptive model. Performance is the percentage of positive responses that the model predicts for a given predictor profile. Evidence is the number of customers who exhibited statistically similar behavior. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision

NEW QUESTION # 20
An online store is interested in increasing its revenues from cross-selling and wants to predict the acceptance rate of the offers presented on their website. A customer's propensity to accept an offer increases when_________.

• A. The offer was accepted by similar customers
• B. Similar offers were rejected by the customer
• C. The offer was rejected by similar customers
• D. Similar offers were accepted by the customer

Answer: D

Explanation:
Explanation
This is because a customer's propensity to accept an offer depends on their past behavior and preferences. If a customer has accepted similar offers in the past, they are more likely to accept a new offer that matches their interests
https://academy.pega.com/sites/default/files/media/documents/2020-12/Mission20301-2-EN-StudentGuide.pdf

NEW QUESTION # 21
Which value is output by an Adaptive Model?

• A. Score
• B. Performance
• C. Lift
• D. Behavior

Answer: D

Explanation:
Explanation
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.
References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/using-adap

NEW QUESTION # 22
Pega machine learning supports the creation of which two distinct types of predictive models? (Choose Two)

• A. Binary
• B. Categorical
• C. Numerical
• D. Continuous

Answer: A,B

Explanation:
Explanation
Pega machine learning supports the creation of two distinct types of predictive models: categorical and binary.
Categorical models predict the outcome of a variable that can have multiple values, such as product category or customer segment. Binary models predict the outcome of a variable that can have only two values, such as yes or no, accept or reject, etc. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision

NEW QUESTION # 23
A company wants to capture the sentiment of messages to allow its customer service representatives to focus on only the negative messages. Sentiment refers to the general attitude of the author towards a subject and can be________________

• A. negative
• B. absent
• C. defensive
• D. offensive

Answer: A

Explanation:
Explanation
Sentiment refers to the general attitude of the author towards a subject and can be negative.

NEW QUESTION # 24
Results of two simulations can be compared using the___________.

• A. C
  Proposition Distribution report Reference:
  The Proposition Distribution report is used to compare the results of two simulations.
• B. Proposition Distribution report
• C. Visual Business Director
• D. Predictive Analytics Director
• E. Interaction History report

Answer: A

NEW QUESTION # 25
.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. the Not keywords function as negative features
• B. the Must keywords are required to detect the topic
• C. the keywords are ignored
• D. keywords and training data have a similar impact on the model

Answer: A

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 # 26
What two tasks does a system architect need to perform to export historical data? (Choose Two)

• A. Switch to a resilient repository
• B. Create a data set
• C. Validate the predictors used by the adaptive models
• D. Set the sample percentage for positive and negative outcomes
• E. Export the data set

Answer: B,E

Explanation:
Explanation
Two tasks that a system architect needs to perform to export historical data are export the data set and create a data set.

NEW QUESTION # 27
Model transparency is becoming an important requirement for many businesses. In Prediction Studio, model transparency thresholds can be set for

• A. a model type
• B. a department
• C. a business issue
• D. a model

Answer: D

Explanation:
Explanation
In Prediction Studio, model transparency thresholds can be set for a model.

NEW QUESTION # 28
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 # 29
You are the Decisioning Consultant on an Al-powered one-to-one Customer Engagement implementation project. You are asked to design the Next-Best-Action prioritization expression that balances the customer needs with the business objectives.
What factors do you consider in the prioritization expression?

• A. product eligibility rules
• B. product compatibility rules
• C. customer contact rules
• D. business levers

Answer: D

Explanation:
Explanation
Business levers are factors that you consider in the prioritization expression to balance the customer needs with the business objectives. They can include revenue, cost, risk, retention, satisfaction, or any other custom metric that reflects the value of an action. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/using-business-

NEW QUESTION # 30
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?

• A. Case management
• B. Customer Decision Hub
• C. Text analysis
• D. Adaptive prediction

Answer: B

Explanation:
Explanation
Customer Decision Hub Reference:
To optimize the click-through rate of a web banner, you need to create a Customer Decision Hub prediction.

NEW QUESTION # 31
The decision components use on the strategy canvas can be individually configured.
Which function is available when configuring the Group By component?

• A. Divide
• B. Multiply
• C. True if Some
• D. Count

Answer: D

Explanation:
Explanation
According to the Pega Academy1, decision strategies drive the next best action and comprise a unit of reasoning represented by decision components. You use the Proposition Data component to import actions into a strategy canvas. The sequence of the components in the canvas determines which action is selected for a customer.
The Group By component2 is used to group a list of ranked items based on a field and retain only one element in each group. The function available when configuring the Group By component is Count2, which returns the number of elements in each group.

NEW QUESTION # 32
A large online store uses Pega Customer Decision Hub to smoothly adapt to changing customer behavior.
Adaptive models help accomplish this business objective as the models learn from customer responses.
Which statement about adaptive models is correct? s

• A. Adaptive models perform a binary model calculation
• B. Adaptive models require a historical data set to start learning
• C. Adaptive models perform a continuous model calculation
• D. Adaptive models require underlying predictive models

Answer: A

Explanation:
Explanation
Adaptive models perform a binary model calculation. This means that adaptive models predict the likelihood of a positive or negative response for each action and customer profile. Adaptive models do not require underlying predictive models or historical data sets to start learning. They learn from customer responses in real time and continuously update their predictions. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision

NEW QUESTION # 33
In a decision strategy, the Adaptive Model decision component belongs the

• A. Predictive Model category
• B. Arbitration category
• C. Decision Analytics category
• D. Business Rules category

Answer: C

Explanation:
Explanation
In a decision strategy, the Adaptive Model decision component belongs to the Decision Analytics category.
This category contains components that use advanced analytics techniques, such as adaptive models, predictive models, text analytics models, etc., to make predictions or recommendations. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/decision-analyt

NEW QUESTION # 34
When implementing a Next-Best-Action project, which step is recommended to be taken first?

• A. Define prioritization formula
• B. Define Issue and Group hierarchy
• C. Define business rules
• D. Define propositions

Answer: B

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 # 35
What is the key component of a Next-Best-Action strategy?

• A. Decision table
• B. Work flow
• C. Predictive model
• D. Strategy

Answer: D

Explanation:
Explanation
The key component of a Next-Best-Action strategy is a strategy, which is a graphical representation of the business logic that determines which actions to offer to each customer and in what order. A strategy can use various components, such as business rules, predictive models, filters, prioritizers, etc., to achieve this goal.
References: https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer

NEW QUESTION # 36
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