Scaling Data Before PCA
When dealing with data that has features with different scales, it's often important to scale the data first. This is because data that has larger values may sway the data even with relatively little variability.
The combine
data frame is loaded for you.
This exercise is part of the course
Linear Algebra for Data Science in R
Exercise instructions
- Use the
scale()
function to scale the 5th through the 12th columns ofcombine
data. Name this data frameB
and show some of the values usinghead()
. - Use
prcomp()
to perform principal component analysis on the data and summarize this analysis usingsummary()
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Scale columns 5-12 of combine
B <- ___(___[, 5:12])
# Print the first 6 rows of the data
___
# Summarize the principal component analysis
summary(____(B))