iSQI CT-AI Exam - Topic 6 Question 45 Discussion

The ISTQB CT-AI syllabus explains in Section1.6 -- Machine Learning Approachesthatsupervised learningis appropriate when labeled data exists and the goal is to predict an output based on known historical examples. Predicting a customer'spurchase probabilityis aclassificationtask when the output corresponds to discrete categories such as''likely to purchase''vs.''not likely to purchase.''The syllabus gives similar examples in describing classification as the process of assigning instances to predefined classes based on learned patterns in labeled data. Because the retail company wants to determine whether a customer will make a purchase based on marketing actions, classification is the most appropriate choice .

Option A (regression) predicts continuous numeric values and is less suitable because the task centers oncategorical likelihood, not estimating exact monetary values. Option C (unsupervised learning) is used when labels are not available---here, the company has labeled purchase histories. Option D (reinforcement learning) requires an interactive environment with reward-driven behavior, which is not applicable to this scenario.

Thus,supervised learning (classification)is the most suitable approach according to the syllabus.