Ridge Regression

Ridge regression is a regularized variation of linear regression designed to produce more stable estimates, especially in datasets with many features. By penalizing coefficient magnitudes, it prevents excessively large parameter values and reduces the risk of overfitting. It often generalizes better than ordinary linear regression when multicollinearity is strong. However, because it keeps all features in the model, it does not perform feature selection; instead, it shrinks coefficients in a controlled manner.