What are the main categories of dimensionality reduction techniques?
Dimensionality reduction is a process of transforming high-dimensional data into lower-dimensional data while preserving some essential features or information. It is a useful technique for machine learning, as it can reduce noise, improve performance, and facilitate visualization and interpretation. In this article, you will learn about the main categories of dimensionality reduction techniques and how they differ.