Idea of principal component analysis (PCA) is:
To reduce the dimensionality of a data set consisting of a large number of interrelated variables
Also, retaining as much as possible of the variation present in the data set.
This is achieved by transforming to a new set of variables, the principal components (PCs), which are uncorrelated.
Download PDF file of presentation here:
https://www.jaeronline.com/6-principal-component-analysis/
