Free Pegasystems PEGACPDS88V1 Practice Exam with Questions & Answers | Set: 4

 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

A solid arrow from a “Set Property” component to a “Filter” component means that a property from the “Set Property” component is referenced by the “Filter” component. For example, you can use a “Set Property” component to calculate a customer’s age and then use a “Filter” component to remove actions that are not suitable for that age group. References: https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/setting-properties

An adaptive model is different from a predictive model as it can use strategy properties as predictors. Strategy properties are dynamic values that are calculated or derived during the execution of a decision strategy. They can capture customer context, such as channel, location, time, etc. References: https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-models-overview

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

The purpose of predictions is to build adaptive models.

Customer Decision Hub Reference:

To optimize the click-through rate of a web banner, you need to create a Customer Decision Hub prediction.

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

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-levers