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?
This exercise is part of the course
Unsupervised Learning in R
Hands-on interactive exercise
Turn theory into action with one of our interactive exercises
