midScikit-Learn
What is feature scaling and why is it important?
Updated May 17, 2026
Short answer
Feature scaling normalizes data ranges to improve model performance.
Deep explanation
Algorithms like SVM and KNN depend on distance metrics, so scaling ensures fair contribution of features.
Real-world example
Used in recommendation systems to normalize user ratings.
Common mistakes
- Not scaling before distance-based algorithms.
Follow-up questions
- Which models don't need scaling?
- Difference between normalization and standardization?