What is the key difference between a predictive model and a human expert?
When building a predictive model, what is a valid predictor data type?
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
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
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
Evidence an assessment of its viability, the Adaptive Model produces three outputs: Propensity, Performance and what is evidence in the context of an Adaptive Model? Performance and what is evidence in the context of an Adaptive Model?
Evidence is the number of customers who exhibited statistically similar behavior to the current customer and responded to the modeled offer. It indicates how reliable the propensity score is based on the available data. Reference: https://academy.pega.com/module/predicting-customer-behavior-using-real-time-data-archived/topic/adaptive-models-overview
Through analysis of customer lifecycles, Next-Best-Action
Through analysis of customer lifecycles, Next-Best-Action anticipates retention issues and takes proactive actions to prevent customer churn. It uses predictive analytics to identify customers who are at risk of leaving and offers them incentives or solutions to retain them. Reference: https://academy.pega.com/module/one-one-customer-engagement/topic/proactive-retention
