A retailer wants to predict, before checkout, whether a current online shopper will finish the purchase or abandon the cart. Which broad type of machine learning problem best fits this use case?
Reinforcement learning optimization
Unsupervised clustering
Classification (binary)
Regression forecasting
The goal is to predict one of two discrete outcomes-purchase or abandonment-for each active shopper. Problems that assign items to a limited set of categories are classification tasks; when the categories are only two, it is binary classification. Regression is for predicting continuous numeric values, clustering is for grouping unlabeled data into similar clusters, and reinforcement learning focuses on sequential decision-making through trial and error rather than one-time predictions.
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