MATLAB Implementation of Feature Dimensionality Reduction Methods
Feature dimensionality reduction techniques including Principal Component Analysis (PCA) and feature selection methods such as SFFS (Sequential Floating Forward Selection), SBS (Sequential Backward Selection), and SFS (Sequential Forward Selection). These four commonly used dimensionality reduction approaches help optimize datasets by reducing feature dimensions while preserving critical information.