Principal Components Analysis

PCA is used to reduce high dimensional data set to lower dimensions. PCA can be used to identify patterns in data, express the data in a lower dimensional space. That way, similarities and differences can be highlighted. It is mostly used in face recognition and image compression. There are several flaws one has to be aware of when working with PCA:

Parallelization strategy

Design of packages