What is feature scaling in unsupervised learning?

Updated May 15, 2026

Short answer

Feature scaling normalizes data to ensure equal feature contribution.

Deep explanation

Algorithms like KMeans rely on distance metrics, so scaling prevents bias.

Real-world example

Scaling age and income before clustering customers.

Common mistakes

  • Skipping scaling before distance-based models.

Follow-up questions

  • What are scaling methods?
  • Why is scaling important?

More Unsupervised Learning interview questions

View all →