[2023年11月14日]Pegasystems PEGACPDS88V1リアル試験問題と解答を無料で提供いたします
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質問 # 60
Lift is key metric for the performance of the adaptive models.
To measure lift, you need a____________
- A. Control group with a new action
- B. Standard model as a benchmark
- C. Control group with random actions
- D. New adaptive model
正解：C
解説：
Explanation
Lift is a key metric for the performance of the adaptive models. To measure lift, you need a control group with random actions. Lift is the ratio of the performance of the adaptive model to the performance of the control group. A control group is a subset of customers who receive random actions instead of the ones suggested by the model. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#data-/data-adm-/data-adm-model
質問 # 61
Which statement about the PMML standard is correct?
- A. The PMML standard can only be used to describe tree, scorecard and regression models.
- B. The PMML standard is designed to facilitate the exchange of scores between applications
- C. The PMML standard is designed to facilitate the exchange of models between applications
- D. The PMML standard is a proprietary standard
正解：C
解説：
Explanation
The PMML standard is designed to facilitate the exchange of models between applications.
質問 # 62
.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 Must keywords are required to detect the topic
- B. the Not keywords function as negative features
- C. keywords and training data have a similar impact on the model
- D. the keywords are ignored
正解：B
解説：
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
質問 # 63
What is the key component of a Next-Best-Action strategy?
- A. Work flow
- B. Strategy
- C. Decision table
- D. Predictive model
正解：B
解説：
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
質問 # 64
When defining outcomes for an Adaptive Model you must define
- A. behavior values to be ignored
- B. one or more positive behavior values
- C. only negative behavior values
- D. positive, negative and neutral behavior values
正解：B
解説：
Explanation
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. References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/configuring
質問 # 65
A Scoring Model allows you to differentiate between
- A. Accept, Reject, Maybe Later
- B. Good, Bad, Unknown
- C. Good, Better, Best
- D. Good, Bad
正解：C
解説：
Explanation
A scoring model allows you to differentiate between Good, Better, and Best outcomes for a given proposition or action. A scoring model assigns a numerical value to each outcome based on its desirability or profitability for the business. References:
https://academy.pega.com/module/predictive-analytics/topic/using-scoring-models
質問 # 66
The standardized model operations process (MLOps) lets you replace a low-performing predictive model that drives a prediction with a new one.
Which feature of MLOps lets you monitor the new model in the production environment without affecting the business outcomes?
- A. Change request
- B. Shadow mode
- C. Historical data capture
- D. Connection to machine learning services
正解：B
解説：
Explanation
This is because shadow mode allows you to test a new model in parallel with an existing model without affecting the decision outcomes. You can compare the performance of both models and decide whether to replace or keep the existing model.
https://academy.pega.com/sites/default/files/media/documents/2020-12/Mission20301-2-EN-StudentGuide.pdf
質問 # 67
Proactive retention is applicable when a customer is
- A. Likely to churn
- B. In a collections process
- C. Initiating contact to churn
- D. A high value customer
正解：A
解説：
Explanation
Proactive retention is applicable when a customer is likely to churn. Proactive retention is a strategy that aims to prevent customer attrition by identifying customers who are at risk of leaving and offering them incentives or solutions to retain them. Proactive retention requires predicting the customer's churn risk and selecting the next best action accordingly. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#decisioning-/decisioning-strategi
質問 # 68
As a data scientist, you are tasked with creating a new prediction that estimates a customers' likelihood to leave the business in the near future. The NBA analyst wants to move forward and use the prediction in Pega Customer Decision Hub to test the application. To unblock the NBA specialist, which task do you prioritize?
- A. Create a placeholder scorecard to drive the prediction
- B. Create the predictive model that drives the prediction
- C. Create the prediction
- D. Create the customer data model
正解：B
解説：
Explanation
To unblock the NBA specialist, as a data scientist, you should prioritize creating the predictive model that drives the prediction.
質問 # 69
Acquiring new customers can be more costly than retaining active customers. U+ Bank uses Pega Customer Decision Hub for its customer engagement and wants to reduce the churn rate by identifying high churn risk customers and making them a retention offer.
To meet this requirement, which two artifacts created by a data scientist allow the NBA specialist to implement the decision strategy? (Choose Two)
- A. A predictive model
- B. An adaptive model
- C. A prediction
- D. A control group
正解：A、D
解説：
Explanation
According to the Data Scientist Student Guide1, page 18, the correct answer is B. A predictive model and C. A control group. A predictive model is a mathematical representation of a real-world process that can be used to predict an outcome based on input data. A control group is a subset of customers who are not exposed to a treatment (such as an offer) and are used to measure the effectiveness of the treatment by comparing their behavior with the treated group.
質問 # 70
The Predictive Model Markup Language (PMML) allows for predictive models to
- A. Perform better
- B. Be easily shared between applications
- C. Be developed faster
- D. Use the same modeling process
正解：B
解説：
Explanation
The Predictive Model Markup Language (PMML) allows for predictive models to be easily shared between applications. PMML is a standard XML format that describes the input parameters, output score, and mathematical formulas of predictive models. PMML enables interoperability between different tools and platforms that support PMML, such as Pega Customer Decision Hub. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#data-/data-predictivemodel-/data-
質問 # 71
Which decision component allows you to monitor the real-time performance of a third- party Churn Model?
- A. Predictive Model
- B. Adaptive Model
- C. Scorecard Model
- D. PMML Model
正解：C
解説：
Explanation
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. References:
https://academy.pega.com/module/predictive-analytics/topic/using-scorecard-models
質問 # 72
When building a predictive model, at what stage do you compare the performance of predictive models?
- A. Model Development stage
- B. Model Export stage
- C. Model Analysis stage
- D. Model Comparison stage
正解：D
解説：
Explanation
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). References:
https://academy.pega.com/module/predictive-analytics/topic/comparing-predictive-models
質問 # 73
When you create a decision strategy from scratch and want to associate an adaptive model with each action, you need to_______.
- A. Create an adaptive model rule for each action
- B. Capture the customer's response
- C. Link all actions with an adaptive model decision component
- D. Define the adaptive model instances in Adaptive Decision Manager
正解：D
解説：
Explanation
To associate an adaptive model with each action in a decision strategy created from scratch, you must define the adaptive model instances in the Adaptive Decision Manager.
質問 # 74
Prediction Studio supports keyword-based topic detection, model-based topic detection and the combination of these. When using machine learning,
- A. the Must keywords function as positive features
- B. keywords have a higher impact on the model than the training data
- C. the Must keywords are required to detect the topic
- D. the keywords are ignored
正解：A
解説：
Explanation
When using machine learning, the Must keywords function as positive features.
質問 # 75
Which component(s) do you use to calculate the average margin of four actions?
- A. one Group By component
- B. one Set Property component
- C. four Set Property components
- D. four Group By components
正解：B
解説：
Explanation
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. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/setting-properti
質問 # 76
What is the key difference between a predictive model and a human expert?
- A. Humans are better at dealing with structured data and identifying patterns.
- B. Predictive models are more capable of detecting patterns in historical data.
- C. Humans make successful predictions on a large amount of data.
- D. Predictive models always outperform human experts.
正解：A
質問 # 77
The mapping of the input fields of a third-party predictive model is done in the
- A. Predictive Model decision component
- B. Predictive Model rule
- C. Predictive Analytics Director portal
- D. Customer class definition
正解：B
解説：
Explanation
The mapping of the input fields of a third-party predictive model is done in the Predictive Model rule. The Predictive Model rule defines how to invoke and interpret the results of a third-party predictive model that is imported in PMML format. References:
https://academy.pega.com/module/predictive-analytics/topic/using-pmml-models
質問 # 78
Which property is automatically recomputed for each decision component?
- A. Priority
- B. Rank
- C. Property
- D. Order
正解：B
解説：
Explanation
The rank property is automatically recomputed for each decision component. It indicates the order in which the actions are presented to the customer, based on their priority and propensity. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/ranking-actions
質問 # 79
U+ Bank promotes credit card offers on its website and uses Pega Customer Decision Hub to personalize the offer for every customer. Now, the bank wants to lower the number of customers that leave the bank by showing a proactive retention offer to high churn risk customers instead. As an NBA analyst, you are tasked with creating a new applicability setting to comply with the new business rule. Which business issue or issues do you modify?
- A. No modification is required
- B. The Sales issue
- C. The Sales issue and the Retention issue
- D. The Retention issue
正解：D
解説：
Explanation
To comply with the new business rule of showing a proactive retention offer to high churn risk customers, you should modify the Retention issue.
質問 # 80
What two tasks does a system architect need to perform to export historical data? (Choose Two)
- A. Export the data set
- B. Validate the predictors used by the adaptive models
- C. Set the sample percentage for positive and negative outcomes
- D. Create a data set
- E. Switch to a resilient repository
正解：A、D
解説：
Explanation
Two tasks that a system architect needs to perform to export historical data are export the data set and create a data set.
質問 # 81
What are the most important aspects taken into consideration when determining the Next-Best-Action?
- A. Market trends and customer satisfaction
- B. Network bandwidth and call duration
- C. Business objectives and customer needs
- D. Product discounts and business profitability
正解：C
解説：
Explanation
The most important aspects taken into consideration when determining the Next-Best-Action are business objectives and customer needs. Business objectives reflect the goals and priorities of the organization, such as increasing revenue, reducing costs, or managing risk. Customer needs reflect the preferences and expectations of the customers, such as their interests, intents, or life events. References:
https://academy.pega.com/module/one-one-customer-engagement/topic/next-best-action-designer
質問 # 82
Which statement about the expected performance of a binary model is correct?
- A. The expected performance must be set before the model can be deployed
- B. The expected performance is calculated automatically when using Pega machine learning
- C. The expected performance of a binary model can range from 0 to 100
- D. It is an optional field
正解：A
解説：
Explanation
The expected performance of a binary model must be set before the model can be deployed.
質問 # 83
An adaptive adaptive model component in a decision: propensity, performance, evidence, and positives.
What is evidence in the context of an adaptive model?
- A. The likelihood of a statistically similar behavior
- B. The number of statistical bins that arc generated by the system
- C. The number of customers who exhibited statistically similar behavior
- D. The number of outcomes that system registered
正解：C
解説：
Explanation
Evidence is the number of customers who exhibited statistically similar behavior. It indicates how much data the model has collected for a given predictor profile. The higher the evidence, the more reliable the model is.
References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision
質問 # 84
When developing a predictive model, the outcome value of a continuous model type can represent__________________
- A. acceptance of an offer
- B. customer churn
- C. customer loan default
- D. the purchase value of an offer
正解：D
解説：
Explanation
When developing a predictive model, the outcome value of a continuous model type can represent the purchase value of an offer.
質問 # 85
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