Question

A retail company has a dataset of 50,000 past customer support emails, each already manually tagged by staff as either 'billing', 'shipping', or 'technical'. The company wants to build a model that automatically assigns one of these three categories to each new incoming email. Which type of machine learning approach best fits this task?

Accepted Answer

Supervised learning, because the model learns from historical examples that already have known category labels

Answer

Unsupervised learning, because the model must discover natural groupings in the email text

Answer

Reinforcement learning, because the model receives rewards for each correctly routed email over time

Answer

Semi-supervised learning, because none of the emails have labels and the model must infer them