What is the difference between Regression and Classification?
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Updated 27 Feb 2026
In Machine Learning, Regression and Classification are two main types of supervised learning techniques. Both use labeled data, but they solve different kinds of problems.
1. What is Regression?
Regression is used when the output is a continuous numeric value.
It answers questions like:
Examples:
Key Point:
Regression predicts numbers.
2. What is Classification?
Classification is used when the output is a category or label.
It answers questions like:
Examples:
Key Point:
Classification predicts labels or categories.
Main Differences Between Regression and Classification
Simple Real-Life Analogy
Imagine a teacher:
When to Use Which?
Use Regression when:
Use Classification when:
Quick Summary
Both are essential techniques in Machine Learning and are widely used in real-world AI applications.