A machine-learning paradigm in which a model is trained on examples that are each paired with a known correct output, learning to predict that output for new, unseen inputs; the paradigm behind most classification and regression tasks.
Facts
Core PrincipleAn algorithm learns to map input data to a specific output from example input-output pairs, so that the trained model can predict outputs for new, unseen data. 1 Connections
Sources
1. Supervised learning - Wikipedia
Lead sectionQuote, Lead section
In machine learning, supervised learning (SL) is a type of machine learning paradigm where an algorithm learns to map input data to a specific output based on example input-output pairs.
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