juniorData Mining
What is dimensionality reduction in data mining?
Updated May 15, 2026
Short answer
It reduces number of features while preserving important information.
Deep explanation
Techniques like PCA and t-SNE reduce feature space to improve visualization, performance, and reduce noise.
Real-world example
Visualizing high-dimensional customer behavior data.
Common mistakes
- Assuming no information loss.
Follow-up questions
- What is PCA?
- What is t-SNE?