Supervised Learning
Technical Definition
Supervised Learning is a machine learning technique where a model is trained on labeled data. The model learns the relationship between input features and the corresponding output labels. Once the model is trained, it can make predictions or classifications on new, unseen data. Supervised learning is commonly used for tasks such as classification (e.g., spam vs. non-spam emails) and regression (predicting a numerical value based on input data). Algorithms like linear regression, decision trees, and support vector machines are commonly used in supervised learning.
Real-World Applications
Medical diagnosis systems use supervised learning to predict diseases based on patient data. For example, a model can be trained on labeled medical records to predict whether a patient has diabetes based on their symptoms and test results. In finance, supervised learning is used to predict stock prices based on historical data.
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