Question: What happens when you use PCA for dimensionality reduction? The principal components may be less interpretable than the original features The principal components are equally

What happens when you use PCA for dimensionality reduction?
The principal components may be less interpretable than the original features
The principal components are equally as interpretable as the original features
The principal components contain the same information as the original features
The principal components may lose some information in comparison to the original features

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