Pegasystems PEGACPDS88V1 Exam Questions Instant Access

Question 1

Which statement about predictive models is true?

APredictive models need historical data to be created

BPredictive models need to be specified in a data attribute

CPredictive models are always associated with an action

DPredictive models need unstructured bie data

Answer : A

Predictive models need historical data to be created. Predictive models are statistical models that use historical data to learn patterns and trends and make predictions for future outcomes. Predictive models can be built with Pega machine learning or imported from third-party tools such as PMML or H2O. Reference: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision-predictivemodel/main.htm

Question 2

A large online store uses Pega Customer Decision Hub to smoothly adapt to changing customer behavior. Adaptive models help accomplish this business objective as the models learn from customer responses.

Which statement about adaptive models is correct? s

AAdaptive models perform a binary model calculation

BAdaptive models require underlying predictive models

CAdaptive models require a historical data set to start learning

DAdaptive models perform a continuous model calculation

Answer : A

Adaptive models perform a binary model calculation. This means that adaptive models predict the likelihood of a positive or negative response for each action and customer profile. Adaptive models do not require underlying predictive models or historical data sets to start learning. They learn from customer responses in real time and continuously update their predictions. Reference: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision-adaptivemodel/main.htm

Question 3

Results of two simulations can be compared using the___________.

AAnswer :
Visual Business Director

BAnswer :
Interaction History report

CAnswer :
Proposition Distribution report

DAnswer :
Predictive Analytics Director

Answer : C

TheProposition Distribution reportis used to compare the results of two simulations.

Question 4

A company wants to simulate decisions that requires large amounts of dat

a. However, the organisation's live data is inaccessible. Your advice is to use a Monte Carlo data set. The Monte Carlo method

Aenables the company to generate random data for most of its application needs

Bgenerates data that the company can use as input for adaptive decisioning

Ccombines external data sets into a larger data set

Dmakes the organization's live data accessible

Answer : B

The Monte Carlo method enables the company to generate data that simulates customer behavior and can be used as input for adaptive decisioning. The generated data is based on predefined probabilities and distributions that reflect realistic scenarios. Reference: https://academy.pega.com/module/demonstrating-adaptive-learning-archived/topic/creating-monte-carlo-data-set

Question 5

A best practice in data science is to use a control group. What business metric is supported by this practice?

AThe lift that the prediction generates

BThe number of responses

CThe performance of the prediction

DThe success rate of the prediction

Answer : A

The lift that the prediction generates Reference:

Using a control group is a best practice in data science that supports the business metric ofthe lift that the prediction generates.

Question 6

Predictions combine predictive analytics and best practices in data science. As a data scientist, what is a valid reason to adjust the default response timeout in a prediction?

ASuit the use case

BOptimize the success rate

CIncrease lift

DLimit the number of responses

Answer : A

As a data scientist, a valid reason to adjust the default response timeout in a prediction is tosuit the use case.

Question 7

The outcome of a scoring model indicates the likely

Awrite-off value of an arrears case

Bclaim value of a health insurance

Cperiod in which a spare part has to be replaced

Dresponse to an offer

Answer : D

The outcome of a scoring model indicates the likely response to an offer that is presented to a customer. For example, a scoring model can predict if a customer will accept, reject, or defer an offer for a credit card upgrade. Reference: https://academy.pega.com/module/predictive-analytics/topic/using-scoring-models

Pegasystems Certified Pega Data Scientist 8.8 PEGACPDS88V1 Exam Questions