Additional results of PCA
PCA models in R produce additional diagnostic and output components:
center
: the column means used to center to the data, orFALSE
if the data weren't centeredscale
: the column standard deviations used to scale the data, orFALSE
if the data weren't scaledrotation
: 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 componentsx
: 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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