As we only need to retain the principal components that account for most of the variance of the original features, we can either use the Kaiser method, scree test, or the percentage of variation explained as the selection criteria. The main purpose of a scree test is to graph the component analysis results as a scree plot and find where the obvious change in the slope (elbow) occurs. In this recipe, we will demonstrate how to determine the number of principal components using a scree plot.
Determining the number of principal components using the scree test
Getting ready
Ensure that you have completed the previous recipe by generating a principal component object and save it in the variable, swiss.pca.
