Preference learning

Preference learning is a type of machine learning that focuses on understanding and predicting individual preferences or choices. Instead of predicting exact outcomes, it learns from comparisons—such as which option someone prefers over another—to model their tastes. This approach is useful in recommendations, like suggesting movies or products, by capturing what users like based on their past comparisons. It helps systems make personalized suggestions that align closely with individual preferences, improving relevance and user satisfaction.