# Score of importance from feature selection techniques

Can I get the score of importance for each feature in feature selection methos such as Chi2, Information Gain (IG), or Recursive Feature Elimination (RFE)? Or they just provide a list of important features?

I don't use scikit-learn so I can't speak to the specifics on that, but the R package CORElearn will give you importance values (usually on [0,1] I think) for features using information gain, minimum description length, and a whole host of others. Might be of interest to check that package out if scikit-learn can't provide what you are seeking.

As far as I know, in scikit-learn you can only get individual (relative) features importance if you're using an ensemble method of decision trees. After fitting a model you can check model.feature_importances_. As in the example below:

# Feature Importance
from sklearn import datasets
from sklearn import metrics
from sklearn.ensemble import ExtraTreesClassifier