Original Post Principal Component Regression (PCR) is a variation of multiple linear regression. This method utilizes the characteristics of Principal Component Analysis (PCA) to address the issue of multicollinearity in multiple linear regression. The core algorithm involves combining multiple features into principal components (PCs) and performing regression analysis. The PCs used here possess..
