Free Pegasystems PEGACPDS88V1 Exam Dumps August 2026

When building a predictive model, the Data Analysis stage is where you select the input data that will be used to train and test the model. You can also filter, group, or transform the input data to improve its quality and relevance. Reference: https://academy.pega.com/module/predictive-analytics/topic/analyzing-data

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. Reference: https://academy.pega.com/module/creating-and-understanding-decision-strategies-archived/topic/using-business-levers

Adaptive model predictors are selected from the customer profile, which contains information about the customer's attributes and behavior. Predictors can be either scalar or aggregate properties that capture customer context, such as channel, location, time, etc. Reference: https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/configuring-adaptive-models

TheSwitchcomponent allows you to use a third-party Credit Risk Model 80% of the time and a Pega Credit Risk Model 20%.

The Pega Customer Decision Hub delivers Next-Best-Actions consistently through multiple channels. This applies toMobilechannels.

When you increase the performance threshold setting of an adaptive model rule, the number of active predictors may decrease. The performance threshold is the minimum performance that a predictor must have to be included in the model. If you increase this value, some predictors may not meet the criteria and be excluded from the model. Reference: https://community.pega.com/sites/default/files/help_v82/procomhelpmain.htm#rule-/rule-decision-/rule-decision-adaptivemodel/main.htm

Sentiment refers to the general attitude of the author towards a subject and can benegative.

The PMML standard is designed tofacilitate the exchange of models between applications.