In a scenario where dimensionality reduction is essential but preserving the original features' meaning is also crucial, how would you approach using PCA?
- You would avoid PCA and use another method
- You would carefully interpret the principal components in terms of original features
- You would perform PCA on a subset of the original features
- You would use PCA without considering the original features' meaning
In this scenario, careful interpretation of the principal components in terms of the original features would be the key to preserve their meaning while still benefiting from dimensionality reduction.
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