Standard stepwise regression combines attributes of both forward selection and backward elimination.

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Stepwise regression is a method of fitting regression models in which the choice of predictive variables is carried out by an automatic procedure that involves both forward selection (adding variables one at a time based on some criterion) and backward elimination (removing variables one at a time based on some criterion).

Standard Stepwise Regression Combines Attributes of Both Forward Selection and Backward