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What Is Supervised Learning?
ML that learns from labeled examples to make predictions.
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AiTechWorlds
AiTechWorlds
Supervised learning is machine learning that learns from labeled examples to make predictions. This visual guide covers labeled data, classification vs regression, training and testing, evaluation metrics, and common supervised algorithms.
ML that learns from labeled examples to make predictions.
Each example includes the correct answer.
Features are inputs; the label is the target.
Classification and regression.
Predict a category, like spam or not spam.
Predict a number, like house price.
The model adjusts to reduce prediction error.
Test on unseen data to measure real performance.
Memorizing training data hurts new predictions.
Too simple a model misses patterns.
How often predictions are correct.
Quality vs completeness of positive predictions.
Shows correct and wrong predictions by class.
Fit a line to predict numbers.
Predict probabilities for classes.
Split data with yes/no questions.
Classify by nearest labeled neighbors.
Find the best boundary between classes.
Spam filters, pricing, and diagnosis.
Try regression and classification on a sample dataset.
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