Question 28
Domain 1 — AI Concepts, Terminology, and Use CasesMachine Learning, Advanced Course: A company wants to use machine learning to predict customer churn based on past behavior. Which aspect of neural networks makes them suitable for this task?
Correct answer: A
Explanation
Neural networks are suited for churn prediction because they can learn "complex patterns in data" from past customer behavior. This lets them model nonlinear relationships and interactions among features that simpler methods may miss.
Why each option is right or wrong
A. Their ability to identify complex patterns in data
Neural networks are designed to learn nonlinear relationships and higher-order feature interactions from historical inputs, which is exactly what churn prediction requires when customer behavior signals are not linearly separable. In practice, this means they can extract complex patterns from variables such as usage frequency, purchase history, and support interactions that simpler models may fail to combine effectively.
B. Their capability to store large amounts of customer data
C. Their ability to replace traditional databases
D. Their speed in processing simple calculations