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PEGACPDS88V1
Certified Pega Data Scientist 8.8 Questions and Answers

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Questions # 31:

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

Options:

a model type

a model

a department

a business issue

Answer

Explanation

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

Questions # 32:

To measure the boost in success rate AI generates, you need

Options:

a control action that is offered to random customers

a control action that is offered to a fixed group of customers

a control group of customers that receive a standard action

a control group of customers that receive a random action

Answer

Explanation

To measure the boost in success rate AI generates, you need a control action that is offered to random customers.

Questions # 33:

Which decision component enables you to use a PMML model?

Options:

Predictive Model

PMML Model

Third-party Model

Adaptive Model

Answer

Explanation

The decision component that enables you to use a PMML model is Predictive Model. Predictive Model is a component that references a predictive model rule that defines the input parameters and the output score of the model. You can use a predictive model component to reference a PMML model that is imported from a third-party tool and use it in your decision strategy. References: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision-predictivemodel/main.htm

Questions # 34:

An adaptive adaptive model component in a decision: propensity, performance, evidence, and positives.

What is evidence in the context of an adaptive model?

Options:

The likelihood of a statistically similar behavior

The number of customers who exhibited statistically similar behavior

The number of statistical bins that arc generated by the system

The number of outcomes that system registered

Answer

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-adaptivemodel/main.htm

Questions # 35:

A telecommunications company wants to apply text analysis to incoming emails to understand how satisfied its customers are with various products and services. That setup requires natural language processing (NLP) of the email texts. What is one of the types of analysis that occurs during natural language processing?

Options:

Presumptive analysis

Intent analysis

Subjective analysis

Semantic analysis

Answer

Explanation

One of the types of analysis that occurs during natural language processing is Semantic analysis.

Questions # 36:

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

Options:

Customer zip code

Historical interaction data

Customer name

Usage data

Answer

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-adaptivemodel/main.htm

Questions # 37:

Pega Adaptive Models_________

Options:

involve a significant human effort to develop

require historical data_________________

learn about customer behavior in real time

can only be used in inbound channels

Answer

Explanation

Pega adaptive models learn about customer behavior in real time by analyzing the responses to each offer and updating their predictions accordingly. They do not require historical data, human effort, or inbound channels to function. References: https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-models-overview

Questions # 38:

.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,_________________.

Options:

the Not keywords function as negative features

the keywords are ignored

the Must keywords are required to detect the topic

keywords and training data have a similar impact on the model

Answer

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

Questions # 39:

The mapping of the input fields of a third-party predictive model is done in the

Options:

Predictive Model decision component

Predictive Model rule

Predictive Analytics Director portal

Customer class definition

Answer

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

Questions # 40:

The Adaptive Model output that is automatically mapped to a strategy property is_________.

Options:

performance

propensity

evidence

score

Answer

Explanation

The adaptive model output that is automatically mapped to a strategy property is propensity, which indicates the likelihood that the customer will accept or respond to an offer. Propensity is also known as behavior or probability in decision strategies. References: https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/using-adaptive-models-decision

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