100%無料PEGACPDS88V1試験問題集リアルPega PCDS問題集142解答を掴み取れ！
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PEGACPDS88V1（Certified Pega Data Scientist 88V1）認定試験は、Pegaの高度な分析ツールを使用して予測モデルを開発し、戦略的意思決定を推進するデータサイエンティストの知識とスキルを評価する包括的な評価です。この試験は、データの準備、モデルの開発、モデルの評価、展開など、さまざまな分野での候補者の熟練度を評価します。この認定は、データ分析、統計学、機械学習の経験を持ち、Pegaのデータサイエンスプラットフォームの専門知識を証明したい個人を対象としています。
質問 # 52
The purpose of model templates when using Pega machine learning is
- A. to set the model context
- B. to streamline model development
- C. to set the model outcomes
- D. to streamline model deployment
正解：B
解説：
Explanation
The purpose of model templates when using Pega machine learning is to streamline model development.
質問 # 53
Pega Customer Decision Hub uses the P*C*V*L arbitration formula to select the next best action for each customer. Which description best describes the purpose of the formula?
- A. To ensure that the customer is always given the best offer, regardless of the business objective
- B. To provide insight into business processes
- C. To ensure that every customer receives the same action
- D. To balance customer needs with business objectives
正解：D
解説：
Explanation
Pega Customer Decision Hub uses the PCV*L arbitration formula to select the next best action for each customer. The purpose of the formula is to balance customer needs with business objectives.
質問 # 54
The likelihood that a proposition will be accepted by the customer is stored in the strategy property called_______.
- A. pyProbability
- B. pyLikelihood
- C. pyBehavior
- D. pyPropensity
正解：C
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 # 55
From two churn models with the similar performance, we chose the one the_____
- A. Highest churn rate
- B. Fewest number of predictors
- C. Most evidence
- D. Highest number of predictors
正解：B
解説：
Explanation
The principle of parsimony states that from two models with similar performance, we choose the one with the fewest number of predictors. This is because a simpler model is easier to understand, maintain, and deploy.
References: https://academy.pega.com/module/predictive-analytics/topic/evaluating-predictive-models
質問 # 56
As a highly experienced data scientist, which two advanced settings are available to you? (Choose Two)
- A. The parameters used to bin the responses
- B. Predictor selection
- C. Outcomes
- D. The update frequency of the models
- E. Predictor types
正解：B、D
解説：
Explanation
Predictor selection and The update frequency of the models Reference:
As a highly experienced data scientist, you have access to advanced settings such as predictor selection and the update frequency of the models
質問 # 57
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 of a binary model can range from 0 to 100
- C. The expected performance is calculated automatically when using Pega machine learning
- 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 # 58
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. Case management_____
- C. Customer Decision Hub
正解：C
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 # 59
When building a predictive model, in which development step is the regression model created?
- A. Model Export
- B. Model Analysis
- C. Model Development
- D. Data Analysis
正解：C
質問 # 60
A strategy designer has created 10 actions in the Sales/Credit Cards group and 10 actions in the Sales/Mortgages group. He would like to import all 10 actions from the Credit Cards group and only two actions from the Mortgage group into one decision strategy. What is the minimum number of Proposition Data components he needs to use in his strategy?
- A. twelve
- B. one
- C. two
- D. three
正解：D
解説：
Explanation
If a strategy designer has created 10 actions in the Sales/Credit Cards group and 10 actions in the Sales/Mortgages group and would like to import all 10 actions from the Credit Cards group and only two actions from the Mortgage group into one decision strategy, the minimum number of Proposition Data components he needs to use in his strategy is three.
質問 # 61
U+ Telecom uses predictive analytics in its retention strategy. You have created a predictive model based on recent historical company data and have placed the new model in shadow mode. Which statement is true about the new predictive model?
- A. The new model does not affect business outcomes
- B. The active model does not affect business outcomes
- C. The active model and the new model affect business outcomes
- D. The new model affects business outcomes
正解：D
解説：
Explanation
The new model does not affect business outcomes Reference:
When you place a new predictive model in shadow mode, it does not affect business outcomes.
質問 # 62
To confirm the continuing accuracy of your adaptive models, adaptive models must be regularly inspected.
Which two tasks are part of a regular inspection? (Choose Two)
- A. Adjust the advanced settings________________
- B. Check the performance and success rate of the models
- C. Add the historical data collected since the last inspection
- D. Update the models______________________________
- E. Check the performance of individual predictors
正解：B、E
解説：
Explanation
To confirm the continuing accuracy of your adaptive models, two tasks that are part of a regular inspection are check the performance and success rate of the models and check the performance of individual predictors.
質問 # 63
.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 keywords are ignored
- C. keywords and training data have a similar impact on the model
- D. the Must keywords are required to detect the topic
正解：A
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 # 64
For an Adaptive Model to react quickly to changes in customer behavior, the
- A. value of the memory setting should be set to a low number
- B. strategy must include the calculation for smooth propensity
- C. performance threshold should be set to a low number
- D. model must always evaluate all customer responses
正解：C
質問 # 65
The result of a Predictive Model is stored in a property called__________.
- A. pxResult
- B. pyPrediction
- C. pxSegment
- D. pyOutcome
正解：C
質問 # 66
To enable an assessment of its reliability, the Adaptive Model produces three outputs: Propensity, Performance and Evidence. The performance of an Adaptive Model that has not collected any evidence is_________.
- A. 1-0
- B. null
- C. 0.0
- D. 0.5
正解：D
解説：
Explanation
When an adaptive model has not collected any evidence, its performance is 0.5, which means that it has no predictive power and is equivalent to a random guess. As more evidence is collected, the performance can increase or decrease depending on how well the model predicts customer behavior. References:
https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-m
質問 # 67
What are two of the results of an adaptive model? (choose two)
- A. Performance
- B. Priority
- C. Segment
- D. Evidence
正解：A、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 # 68
Using Prediction Studio to build Pega machine learning models on historical data, you can build two types of models:____________and____________.
(Choose Two)
- A. adaptive models
- B. voice to text model
- C. continuous models
- D. binary 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 # 69
Which two factors do you inspect to access the general health of the adaptive models in Prediction Studio?
(Choose Two)
- A. Number of responses
- B. Number of decisions
- C. Model transparency
- D. Performance of the models
正解：C、D
解説：
Explanation
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.
質問 # 70
What type of a predictor can you use in an adaptive model?
- A. Integer
- B. Symbolic
- C. Logical
- D. Page Type
正解：B
解説：
Explanation
In an adaptive model, you can use Symbolic predictors.
質問 # 71
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 customers who have responded to the modeled offer
- C. The number of statistical bins used to evaluate the response
- D. The number of customers who exhibited statistically similar behavior
正解：D
解説：
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
質問 # 72
When developing a predictive model, the outcome value of a continuous model type can represent__________________
- A. customer churn
- B. customer loan default
- C. the purchase value of an offer
- D. acceptance of an offer
正解：C
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 # 73
A very important aspect of each model is how good a model or a given predictor is in predicting the required behavior. When building a predictive model, the use of testing and validation samples___________________
- A. enables model validation in strategies
- B. is mandatory for segmentation
- C. increases the accuracy of models
- D. validates the quality of input data
正解：C
解説：
Explanation
A predictive model is a mathematical function that estimates the probability of an outcome based on input data. When building a predictive model, the use of testing and validation samples increases the accuracy of models123. Testing and validation samples are subsets of data that are used to evaluate how well a model performs on new data that was not used to train the model. Testing and validation samples help prevent overfitting, which is when a model learns too much from the training data and fails to generalize to new data.
質問 # 74
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. Visual Business Director
- C. Predictive Analytics Director
- D. Interaction History report
- E. Proposition Distribution report
正解：A
質問 # 75
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. Actions that have a low number of responses
- B. Actions that are offered so often that they dominate other actions
- C. Predictors that are never used
- D. Predictors with a low performance_________
- E. Actions for which the model is not predictive
正解：B、D
解説：
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.
質問 # 76
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