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FRM Part I · FRM Exam Part I · Machine Learning and Prediction

A risk analyst at a bank has a historical dataset of 20,000 consumer loans. Each record contains borrower characteristics and a label showing whether the borrower defaulted within 12 months. She trains a model to predict default for new applicants. Which type of machine learning does this describe?

This is supervised learning. The loan records include a known outcome label, default or no default, and the model learns the relationship between borrower features and that label so it can classify new applicants. Unsupervised learning works without labeled outcomes.

  1. AUnsupervised learning
  2. BSupervised learningCorrect
  3. CReinforcement learning
  4. DDimensionality reduction

Explanation

The data contain labeled outcomes (default or not), and the model learns a mapping from features to those labels. This is supervised learning, specifically classification. Unsupervised learning would have no labels.

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