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CFA Level I · CFA Level I Exam · Introduction to Financial Data Science

An analyst trains a model to predict whether a borrower will default, using historical loans that are each labeled "default" or "no default." This approach is best described as:

This is supervised learning. The historical loans carry labels showing whether each borrower defaulted, so the algorithm learns the relationship between features and a known target. Unsupervised learning would work without labels, and reinforcement learning would rely on rewards from actions rather than labeled examples.

  1. Aunsupervised learning
  2. Bsupervised learningCorrect
  3. Creinforcement learning

Explanation

The training data include a labeled target (default or no default), so the model learns a mapping from features to a known outcome. That is supervised learning. Unsupervised learning has no labeled target, and reinforcement learning learns through rewards from interacting with an environment.

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