Following my introduction to PCA, I will demonstrate how to apply and visualize PCA in R. There are many packages and functions that can apply PCA in R. In this post I will use the function
prcomp from the
stats package. I will also show how to visualize PCA in R using Base R graphics. However, my favorite visualization function for PCA is
ggbiplot, which is implemented by Vince Q. Vu and available on github. Please, let me know if you have better ways to visualize PCA in R.
Computing the Principal Components (PC)
I will use the classical
iris dataset for the demonstration. The data contain four continuous variables which corresponds to physical measures of flowers and a categorical variable describing the flowers’ species.
We will apply PCA to the four continuous variables and use the categorical variable to visualize the PCs later. Notice that in…
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