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Stepwise regression (often called forward or backward regression) involves fitting a regression model and adding or removing predictors based on $t$ statistics, $R^2$ or information criteria to arrive in a *stepwise* manner at a final model. This tag can also be used for forward selection, backward elimination & best subsets variable selection strategies.

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Feature subset selection by stepwise regression for a random forest model?

I would like to build a random forest model for regression. I have an abundance of potential features, and I expect only some of them to have a significant impact on the target variable. In addition, …