Least Absolute Shrinkage is Equivalent to Quadratic Penalization

摘要

Adaptive ridge is a special form of ridge regression, balancing the quadratic penalization on each parameter of th model. This paper shows the equivalence between adaptive ridge and lasso (least absolute shrinkage and selection operator). This equivalence states that both procedures produce the same estimate. Least absolute shrinkage can thus be viewed as a particular quadratic penalization.