Dimensionality reduction or dimension reduction is the process of reducing the number of random variables under consideration by obtaining a set of principal variables. It can be divided into feature selection (find a subset of the original variables) and feature extraction (transform the data in the high-dimensional space to a space of fewer dimensions). (Wikipedia)