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Additional results of PCA

PCA models in R produce additional diagnostic and output components:

  • center: the column means used to center to the data, or FALSE if the data weren't centered
  • scale: the column standard deviations used to scale the data, or FALSE if the data weren't scaled
  • rotation: the directions of the principal component vectors in terms of the original features/variables. This information allows you to define new data in terms of the original principal components
  • x: the value of each observation in the original dataset projected to the principal components

You can access these the same as other model components. For example, use pr.out$rotation to access the rotation component.

Which of the following statements is not correct regarding the pr.out model fit on the pokemon data?

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Unsupervised Learning in R

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