Software for Partial Least Squares Regression

This code implements Partial Least Squares Regression (PLSR) functionality and is executable within the MATLAB software environment. PLSR is a regression analysis method particularly effective for handling multivariate linear regression problems, especially when dealing with datasets where the number of dimensions exceeds the sample size, making it highly valuable in practical applications. The implementation demonstrates the complete PLSR algorithm workflow, including key components such as covariance matrix decomposition, iterative calculation of latent variables, and regression coefficient determination. Through examining this code, users can observe the detailed execution process of the PLSR algorithm, gaining deeper insights into the method's underlying principles, mathematical foundations, and practical application scenarios. The code structure includes data preprocessing, component extraction, cross-validation routines, and prediction modules, providing a comprehensive framework for understanding and applying PLSR techniques.