Modification to the LASSO Regression Model via its Bayesian Interpretation

Music City Center 

This study presents a generalized LASSO regression model based on the generalized Laplace (GL) distribution. Within the T-R{Y} framework, a family of GL distributions is developed, with a particular case offering a Bayesian perspective on LASSO. This perspective introduces additional terms to the standard LASSO constraint. These terms are examined geometrically, as well as the impact of the parameters of the GL distribution on the generalized LASSO model. Finally, the model's adaptability and effectiveness in variable selection and prediction are illustrated using a real-world dataset.

LASSO regression

beta-Laplace distribution

T-Laplace family

Variable selection

Prediction 

Section on Statistical Learning and Data Science