Question - What is dimensionality reduction? What are its benefits?
Answer -
Dimensionality reduction is defined as the process of converting a data set with vast dimensions into data with lesser dimensions — in order to convey similar information concisely.
This method is mainly beneficial in compressing data and reducing storage space. It is also useful in reducing computation time due to fewer dimensions. Finally, it helps remove redundant features — for instance, storing a value in two different units (meters and inches) is avoided.
In short, dimensionality 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 and feature extraction.