Supervised Learning
Definition
A machine learning approach where models are trained on labeled data, learning to map inputs to known correct outputs.
Supervised learning is the most common form of machine learning. The training data consists of input-output pairs, and the model learns to predict the correct output for new, unseen inputs. Classification tasks (predicting categories like spam vs. not spam) and regression tasks (predicting continuous values like house prices) are both supervised learning problems. Common algorithms include linear regression, logistic regression, decision trees, random forests, and neural networks. The quality and quantity of labeled training data is critical to performance. Supervised learning powers most real-world ML applications from medical diagnosis to credit scoring.
Related Terms
Machine Learning
A subset of AI where systems learn patterns from data and improve their performance over time withou...
Unsupervised Learning
A machine learning approach where models discover patterns and structure in data without labeled exa...
Loss Function
A mathematical function that measures how far a model's predictions are from the actual target value...
Training Data
The dataset used to teach a machine learning model, consisting of examples from which the model lear...