Principal Component Analysis

Principal Component Analysis, or PCA, is a dimensionality-reduction method that is often used to reduce the dimensionality of large data sets, by transforming a large set of variables into a smaller one that still contains most of the information in the large set. It is the process of computing the principal components and using them to perform a change of basis on the data, sometimes using only the first few principal components and…