midClustering
What is feature scaling and why is it important in clustering?
Updated May 15, 2026
Short answer
Feature scaling ensures all variables contribute equally to distance calculations.
Deep explanation
Clustering algorithms rely on distance metrics. Without scaling, features with larger ranges dominate clustering results, leading to biased clusters.
Real-world example
Scaling income and age before customer segmentation.
Common mistakes
- Applying clustering without normalization.
Follow-up questions
- Which scaling method is best?