What is overfitting in unsupervised learning?
Updated May 15, 2026
Short answer
Overfitting occurs when model captures noise instead of structure.
Deep explanation
Even without labels, models can overfit by forming overly complex clusters.
Real-world example
Too many clusters in customer segmentation.
Common mistakes
- Assuming unsupervised models cannot overfit.
Follow-up questions
- How to prevent it?
- Signs?