Hi,
I am working on a binary classification problem in which both training and
test data are highly imbalanced. In other words, the number of instances
available in one class is far more than the other one.
Would you please let me know which evaluation measure is the best one to
compare different methods in imbalanced situations? Please note that
predicting the label of instances of the class which contains lower
instances is really harder than predicting the labels of the other
instances and I am looking for a evaluation measure which consider this
issue.
I am wondering if you also provide me a reference for your opinions.
Thanks a lot,
Best regards,
Hamed
------------------------------------------------------------------------------
Want fast and easy access to all the code in your enterprise? Index and
search up to 200,000 lines of code with a free copy of Black Duck
Code Sight - the same software that powers the world's largest code
search on Ohloh, the Black Duck Open Hub! Try it now.
http://p.sf.net/sfu/bds
_______________________________________________
Scikit-learn-general mailing list
Scikit-learn-general@lists.sourceforge.net
https://lists.sourceforge.net/lists/listinfo/scikit-learn-general
