title: Scikit-learn SelectFromModel - actually obtain the feature importance scores of underlying predictor
body: <p>I was trying to estimate the feature importance for the classification task I have at hand. What is important for me is to get specific numbers which represent importance of each feature, not just 'pick X features which are most important'.</p>
  
  <p>Obvious choice was to use the tree-based methods which provide nice feature_importances_ method to obtain importance of each feature. But I wasn't satisfied with the results of the tree-base classifiers. I learned that SelectFromModel method is capable to eliminate not important features based on the importance score and successfully does that for SVM or Linear models as well.</p>
  
  <p>I wonder, is there any way to obtain specific importance score from SelectFromModel for each feature instead of just getting a list of most important features?</p>