midScikit-Learn
What is PCA in Scikit-Learn?
Updated May 17, 2026
Short answer
PCA reduces dimensionality by projecting data onto principal components.
Deep explanation
It identifies directions of maximum variance and transforms data into lower dimensions.
Real-world example
Used in image compression and visualization.
Common mistakes
- Applying PCA without scaling data.
Follow-up questions
- What are principal components?
- Does PCA preserve labels?