How do you decide how many PCA components to keep?
easyAnswer
- Look at the cumulative explained-variance ratio and keep enough components to reach a target (e.g., 90% or 95%).
- You can also inspect the scree plot for an elbow, or pick components based on downstream cross-validation performance.
- Standardize features before PCA when they are on different scales.
Check yourself — multiple choice
- Always keep just one component
- Keep components until cumulative explained variance hits a target
- PCA does not need standardization
- Number of components must equal number of features
Cumulative explained variance is the standard criterion.
#dimensionality-reduction
Practise Unsupervised Learning
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