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
Associated With
Source Unsupervised learning - Wikipedia
In Field
Sources
1. Supervised learning - Wikipedia
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.
In Group: Machine Learning Paradigms, Lead
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.
View the SourceUnsupervised learning - Wikipedia
Associated With: Unsupervised Learning, Lead section, first sentenceQuote, Associated With: Unsupervised Learning, Lead section, first sentence
Unsupervised learning is a framework in machine learning where, in contrast to supervised learning, algorithms learn patterns exclusively from unlabeled data.
Reader Challenges (0)
No disputes yet. Spotted an error or a better source? Open the first one.
Sign in to dispute this or suggest a correction.