I am trying to do binary classification of News Articles (Sports/Non-Sports) using recurrent neural net in tensorflow. The training data is highly skewed [Sports:Non-Sports::1:9].
I am using cross-entropy as my cost function, which treats both classes equally.
What are the ways by which user can penalise one class? Or is there any other cost function suitable for this purpose?