For perfectly independent covariates it is equivalent to sorting by p-values. Normalize your features with StandardScaler, and then order your features just by ef_.Use inherently sparse models like ElasticNet or Lasso.There are, however, some pieces of advice for those who still need a good way for feature selection with linear models: Moreover, pure OLS is only one of numerous regression algorithms, and from the scikit-learn point of view it is neither very important, nor one of the best. That's because what is commonly known as 'stepwise regression' is an algorithm based on p-values of coefficients of linear regression, and scikit-learn deliberately avoids inferential approach to model learning (significance testing etc). Scikit-learn indeed does not support stepwise regression.
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