lambdaPenaltyBx
lambdaPenaltyBx is a term that appears in the context of regularization techniques used in machine learning and statistical modeling. Specifically, it refers to a type of penalty term applied to the coefficient of a predictor variable, often denoted as 'x', within a model. The 'lambda' prefix typically signifies a tuning parameter, a hyperparameter that controls the strength of the penalty.
The purpose of a penalty term like lambdaPenaltyBx is to prevent overfitting by shrinking the estimated coefficients
In practice, lambdaPenaltyBx might be a component of more complex regularization methods such as Elastic Net