In machine learning and statistics, dimensionality reduction or dimension reduction is the process of reducing the number of random variables under consideration, and can be divided into feature selection and feature extraction.
In machine learning and statistics, dimensionality reduction or dimension reduction is the process of reducing the number of random variables under consideration,, via obtaining a set "uncorrelated" principle variables. It can be divided into feature selection and feature extraction.