Data Preprocessing Questions
Feature extraction is the process of selecting and transforming relevant features from raw data to create a reduced and more meaningful representation of the data. It involves identifying and extracting the most informative attributes or characteristics that can best represent the underlying patterns or structures in the data. Feature extraction is commonly used in machine learning and data analysis tasks to improve the efficiency and effectiveness of algorithms by reducing the dimensionality of the data and removing irrelevant or redundant features.