The Machine Learning Advent Calendar Day 13: LASSO and Ridge Regression in Excel

Ridge and Lasso regression are often misunderstood as adding complexity to linear models, but in reality, they maintain the same prediction structure while modifying the training objective through regularization penalties. These penalties, applied to the coefficients, promote more stable and robust solutions, particularly when features are correlated, by effectively imposing a preference for certain coefficient values rather than increasing model complexity. Implementing Ridge and Lasso regression step-by-step in Excel demonstrates that regularization techniques do not complicate the model but instead serve as a form of regularization that guides the model toward more stable solutions. This perspective clarifies that the core