Pegasystems PEGACPDS88V1 Exam Dumps

Dates with absolute time/date values, such as birthdays and Numeric data such as customer age and income Reference:

Dates with absolute time/date values, such as birthdaysandNumeric data such as customer age and incomerequire no preprocessing before being used as potential predictors in adaptive analytics.

When building a predictive model, a valid predictor data type is Boolean, which can have only two values: true or false. Other valid predictor data types are numeric, date, and symbolic (categorical). Reference: https://academy.pega.com/module/predictive-analytics/topic/predictor-data-types

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. Reference: https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/using-adaptive-models-decision

Pega Process AI lets you bring your own predictive models to Pega and use predictions in case types to optimize the way your application processes work and meet your business goals.

To use the outcome of a predictive fraud model in the case type that processes the incoming claim, you need to usethe model outcomeinthe condition of a decision step2. This way, you can route suspicious claims to a fraud expert for closer inspection based on the model's prediction.

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