Regularized least squares

Regularized Least Squares is a variant of the standard least squares method used for linear regression that incorporates regularization techniques to prevent overfitting, especially in situations where the model might become too complex relative to the amount of available data. The standard least squares objective function minimizes the sum of the squared differences between observed values and predicted values.