Pegasystems PEGACPDS88V1 Certified Pega Data Scientist 8.8 Online Training
Pegasystems PEGACPDS88V1 Online Training
The questions for PEGACPDS88V1 were last updated at Nov 19,2024.
- Exam Code: PEGACPDS88V1
- Exam Name: Certified Pega Data Scientist 8.8
- Certification Provider: Pegasystems
- Latest update: Nov 19,2024
The purpose of predictions is to______________
- A . build adaptive models
- B . monitor the success rate of individual actions
- C . add best data scientist practices to adaptive models
- D . add predictors to adaptive models
B
Explanation:
The main purpose of predictions is to monitor the success rate of individual actions, by estimating the likelihood of certain outcomes.
When building a predictive model, at what stage do you compare the performance of predictive models?
- A . Model Development stage
- B . Model Analysis stage
- C . Model Export stage
- D . Model Comparison stage
B
Explanation:
Comparing the performance of predictive models typically occurs during the Model Analysis stage.
When building a predictive model, the Data Analysis stage is where you
- A . create data samples
- B . select the input data
- C . group predictors
- D . determine the output field
C
Explanation:
During the Data Analysis stage of building a predictive model, predictors are grouped
A telecom company is interested in improving customer engagement on social media. However, there are hundreds of relevant messages posted every day, and it is not practical for customer service representatives (CSRs) to review and respond to all messages. Instead, CSRs should focus on negative messages.
What do you need to analyze the incoming messages?
- A . Predictive model
- B . Adaptive model
- C . Text categorization model
- D . Text extraction model
C
Explanation:
A text categorization model is a type of text analytics model that can analyze the incoming messages and assign them to predefined categories, such as positive, negative, or neutral sentiment. This way, CSRs can focus on negative messages that require immediate attention or escalation.
References: https://academy.pega.com/module/text-analytics/topic/creating-text-categorization-model
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 . Group By
- B . Filter
- C . Set Property
- D . Prioritize
B
Explanation:
To offer a 10% discount for customers whose CLV value is higher than 400, you should use the Filter strategy component.
As a highly experienced data scientist, which two advanced settings are available to you? (Choose Two)
- A . Outcomes
- B . Predictor types
- C . The parameters used to bin the responses
- D . Predictor selection
- E . The update frequency of the models
C,D
Explanation:
These advanced settings allow a highly experienced data scientist to fine-tune an adaptive model.
Which decision component allows you to monitor the real-time performance of a third- party Churn Model?
- A . Scorecard Model
- B . Adaptive Model
- C . PMML Model
- D . Predictive Model
C
Explanation:
The PMML Model can be used to monitor the real-time performance of a third-party Churn Model
The Predictive Model Markup Language (PMML) allows for predictive models to
- A . Perform better
- B . Be easily shared between applications
- C . Use the same modeling process
- D . Be developed faster
B
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-predictivemodel-pmml/main.htm
Which decision component allows you to use a third-party Credit Risk Model 80% of the time and a Pega Credit Risk Model 20%?
- A . Filter
- B . Champion Challenger
- C . Adaptive Model
- D . Switch
B
Explanation:
The Champion Challenger component is used to implement a setup where multiple models (e.g., a third-party Credit Risk Model and a Pega Credit Risk Model) are used with different weights (80% and 20% in this case).
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 . Any behavior
- C . Positive behavior only
- D . Positive, neutral, and negative behavior
A
Explanation:
Positive and negative behavior
Reference:
To configure an adaptive model, you must identify positive and negative behavior that indicate specific customer behavior.
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