title: Can I simplify the Lasso-Lars runtime for zeroed coefficients?
body: <p>I have a dataset with tens of thousands of features and I use a 2nd order <code>PolynomialFeatures</code> component in my pipeline. When I train with <code>Lasso(Lars)</code> many of these features drop to 0, which is great. However, when I want to use this model in practice for even more features, I would like to avoid the calculation overhead for the 0 coefficients.</p>
  <p>Is there a way in <code>scikit-learn</code> that I can take the result of the <code>Lasso</code> regression coefficients and create a model that only processes the non-zero coefficients when <code>eval</code>uating?</p>