[Q65-Q90] テスト資料PEGACPDS88V1テストエンジン試験問題はここにある[2023年05月]

テスト資料PEGACPDS88V1テストエンジン試験問題はここにある[2023年05月]

合格突破受験者シミュレーションされたPEGACPDS88V1試験PDF問題を試そう

PEGACPDS88V1認定は、Pegaのデータサイエンスと機械学習の能力を誇示するデータサイエンティストにとって貴重な資格です。この業界で認められ、雇用主や同僚から高く評価される認定資格です。この資格は、候補者がPegaのツールや技術を使用して複雑なビジネス問題を解決し、データに基づく意思決定を行う能力を示すものです。

 

質問 # 65
What is the difference between predictive and adaptive analytics?

• A. Adaptive models use the customer data as predict*
• B. Predictive models predict customer behavior.
• C. Predictive models have evidence.
• D. Predictive models can predict a continuous value.

正解：A

解説：
Explanation
The difference between predictive and adaptive analytics is that adaptive models use the customer data as predictors, while predictive models use the customer data as outcomes. Adaptive models learn from real-time customer interactions and update their predictions accordingly. Predictive models use historical customer data to train and validate their predictions. References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m

質問 # 66
To configure an adaptive model, the responses that indicate specific customer behavior must be identified.
What types of behavior need to be identified?

• A. Positive and negative behavior
• B. Positive, neutral, and negative behavior
• C. Any behavior
• D. Positive behavior only

正解：A

解説：
Explanation
Positive and negative behavior Reference:
To configure an adaptive model, you must identify positive and negative behavior that indicate specific customer behavior.

質問 # 67
Which statement about predictive models is true?

• A. They are always associated with a proposition.
• B. They need to be specified in a data attribute.
• C. You need past experience to create a predictive model.
• D. They need unstructured big data.

正解：C

質問 # 68
For an Adaptive Model to react quickly to changes in customer behavior, the

• A. strategy must include the calculation for smooth propensity
• B. value of the memory setting should be set to a low number
• C. performance threshold should be set to a low number
• D. model must always evaluate all customer responses

正解：C

質問 # 69
U+ Bank, a retail bank, offers the Standard card, the Rewards card and the Rewards Plus card to its customers.
The bank wants to display the banner for the offer that each customer is most likely to click; therefore, their Arbitration uses Propensity from the AI models. If you are debugging the Next-Best-Action decision strategy, which strategy component will show you if the result of the Arbitration is correct?

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

正解：C

解説：
Explanation
If you are debugging the Next-Best-Action decision strategy and want to see if the result of the Arbitration is correct, you should use the Prioritize strategy component.

質問 # 70
You can use various data types in adaptive analytics. Some of these require preprocessing before being used as a potential predictor. Others can be used directly. Which two data types require no preprocessing? (Choose Two)

• A. Text data such as Twitter messages
• B. Numeric data such as customer age and income
• C. Symbolic data with up to 200 distinct values, such as products bought previously
• D. Event stream data, such as recent transactions
• E. Dates with absolute time/date values, such as birthdays

正解：B、E

解説：
Explanation
Dates with absolute time/date values, such as birthdays and Numeric data such as customer age and income Reference:
Dates with absolute time/date values, such as birthdays and Numeric data such as customer age and income require no preprocessing before being used as potential predictors in adaptive analytics.

質問 # 71
The likelihood that a proposition will be accepted by the customer is stored in the strategy property called_______.

• A. pyProbability
• B. pyLikelihood
• C. pyPropensity
• D. pyBehavior

正解：D

解説：
Explanation
The likelihood that a proposition will be accepted by the customer is stored in the strategy property called pyBehavior. This property is calculated by an adaptive model or a predictive model and reflects the customer's propensity to respond to an offer. References:
https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/using-predictio

質問 # 72
U+ Insurance uses Pega Process AI and wants straight-through processing of claims with a low fraud risk.
As a data scientist, you create a prediction that calculates the probability that a claim is fraudulent.
What type of prediction do you create to meet this requirement?

• A. A fraud detection prediction
• B. A case management prediction.
• C. A Customer Decision Hub prediction.
• D. A text analytics prediction.

正解：B

解説：
Explanation
to create a prediction that calculates the probability that a claim is fraudulent, you need to create a case management prediction. This type of prediction allows you to use predictive models built on external platforms such as H2O.ai and apply them to case types in Pega Process AI. You can then use the prediction outcome in a decision step to route claims based on their fraud risk.
https://academy.pega.com/challenge/creating-fraud-prediction/v3

質問 # 73
Which adaptive model output is automatically mapped to a strategy property?

• A. Score
• B. Propensity
• C. Evidence
• D. Performance

正解：B

解説：
Explanation
Propensity is the adaptive model output that is automatically mapped to a strategy property. Propensity is the likelihood of a positive response for a given action and predictor profile. It ranges from 0 to 100. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision

質問 # 74
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?

• A. Text analytics prediction.
• B. Sentiment detection does not require any predictions.
• C. Pega Customer Decision Hub prediction.
• D. Case management prediction.

正解：A

解説：
Explanation
To detect the sentiment of the incoming emails, you need to configure a text analytics prediction1234 in 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.

質問 # 75
Using Prediction Studio to build Pega machine learning models on historical data, you can build two types of models:____________and____________.
(Choose Two)

• A. binary models
• B. continuous models
• C. voice to text model
• D. adaptive models

正解：A、D

解説：
Explanation
Using Prediction Studio to build Pega machine learning models on historical data, you can build two types of models: binary models and adaptive models.

質問 # 76
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 # 77
The purpose of predictions is to______________

• A. add best data scientist practices to adaptive models
• B. add predictors to adaptive models
• C. monitor the success rate of individual actions
• D. build adaptive models

正解：A

解説：
Explanation
The purpose of predictions is to build adaptive models.

質問 # 78
The Pega Customer Decision Hub delivers Next-Best-Actions consistently through multiple channels. To which of the following channels does this apply?

• A. Mobile
• B. Traditional newspaper
• C. Cable television
• D. Billboard

正解：A

解説：
Explanation
The Pega Customer Decision Hub delivers Next-Best-Actions consistently through multiple channels. This applies to Mobile channels.

質問 # 79
When developing a predictive model, the outcome value of a continuous model type can represent__________________

• A. customer churn
• B. customer loan default
• C. acceptance of an offer
• 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 # 80
In a decision strategy, the Adaptive Model decision component belongs the

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

正解：B

解説：
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

質問 # 81
Which data is usually not appropriate to be used as a predictor?

• A. Historical interaction data
• B. Customer zip code
• C. Customer name
• D. Usage data

正解：C

解説：
Explanation
Customer name is usually not appropriate to be used as a predictor. A predictor is a property that influences the customer behavior and can be derived from various sources such as customer profile, interaction history, proposition details, etc. Customer name is not likely to have any impact on the customer's preferences or responses, and it may also violate privacy regulations. References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision

質問 # 82
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. customer contact rules
• B. business levers
• C. product eligibility rules
• D. product compatibility rules

正解：B

解説：
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-

質問 # 83
What are two of the results of an adaptive model? (choose two)

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

正解：B、D

解説：
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

質問 # 84
How does a prediction help in proactive retention?

• A. The prediction selects the next best action
• B. The prediction identifies successful offers in past interactions
• C. The prediction suggests the best offer
• D. The prediction predicts the customer's churn risk

正解：D

解説：
Explanation
A prediction helps in proactive retention by predicting the customer's churn risk. A prediction is an estimate of the likelihood of a future outcome based on historical data and statistical models. A prediction can help identify customers who are at risk of leaving and target them with appropriate actions to retain them.
References:
https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#decisioning-/decisioning-strategi

質問 # 85
Which component(s) do you use to calculate the average margin of four actions?

• A. four Set Property components
• B. one Set Property component
• C. four Group By components
• D. one Group By component

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 # 86
U+ Telecom wants to engage in proactive retention to reduce churn. As a data scientist, you create a prediction that calculates the probability that a client is likely to cancel a subscription. What type of prediction do you create?

• A. Text analytics
• B. Customer Decision Hub
• C. Case management_____

正解：B

解説：
Explanation
As a data scientist, you create a prediction that calculates the probability that a client is likely to cancel a subscription. The type of prediction you create is Customer Decision Hub.

質問 # 87
To optimize their customer interactions, U+ Bank routes all emails that are complaints to a specialized department. To identify emails that voice a complaint, the text prediction uses___________

• A. a sentiment model
• B. a language model
• C. An entity extraction model
• D. a topic model

正解：C

解説：
Explanation
To identify emails that voice a complaint, the text prediction uses an entity extraction model.

質問 # 88
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 customer data model
• D. Create the prediction

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 # 89
What type of a predictor can you use in an adaptive model?

• A. Page Type
• B. Integer
• C. Logical
• D. Symbolic

正解：D

解説：
Explanation
In an adaptive model, you can use Symbolic predictors.

質問 # 90
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