Data Science, Factor Analysis, Data, Machine Learning, Statistics.
and it’s read in all non-diagonal values. Interpreting the covariance matrix. The covariance matrix highlights the things that get in the way of seeing patterns in the data. So, at the end of the day, what PCA will produce a set of principal components which: Reduce noise, by maximizing feature