Dimensionality reduction is really a process of cutting down the number of random variables into consideration by obtaining a set of principal variables.[55] To paraphrase, It's really a process of minimizing the dimension of your feature established, also referred to as the "quantity of options".As an example, an algorithm might be fed a lesser am