f1 score of all classes from scikits cross_val_score
For individual scores of each class, use this : 
f1 = f1_score(y_test, y_pred, average= None)
print("f1 list non intent: ", f1)
I'm using cross_val_score from scikit-learn (package sklearn.cross_validation) to evaluate my classifiers.
If I use f1 for the scoring parameter, the function will return the f1-score for one class. To get the average I can use f1_weighted but I can't find out how to get the f1-score of the other class. (precision and recall analogous)
The functions in sklearn.metrics have a labels parameter which does this, but I can't find anything like this in the documentation.
Is there a way to get the f1-score for all classes at once or at least specify the class which should be considered with cross_val_score?