The classifiers in machine learning packages like liblinear and nltk offer a method show_most_informative_features(), which is really helpful for debugging features:
viagra = None ok : spam = 4.5 : 1.0
hello = True ok : spam = 4.5 : 1.0
hello = None spam : ok = 3.3 : 1.0
viagra = True spam : ok = 3.3 : 1.0
casino = True spam : ok = 2.0 : 1.0
casino = None ok : spam = 1.5 : 1.0
My question is if something similar is implemented for the classifiers in scikit-learn. I searched the documentation, but couldn't find anything the like.
If there is no such function yet, does somebody know a workaround how to get to those values?
Thanks a lot!