Data Preprocessing Questions
Dimensionality reduction is the process of reducing the number of features or variables in a dataset while preserving the important information. It aims to simplify the dataset by eliminating irrelevant or redundant features, which can help improve the efficiency and effectiveness of data analysis and machine learning algorithms. This reduction can be achieved through techniques such as feature selection or feature extraction, which transform the original high-dimensional data into a lower-dimensional representation.