I am currently assessing the performance of a logit classifier, and I
wonder why is the “average” option, for the F-score metric, is not taken
into account when using a binary classifier. I am talking about line 1091
of metrics.py (sklearn.metrics):
elif n_labels == 2 and pos_label is not None:
after entering this “if”, the F-score of the positive label is returned,
without taking into account the macro (or micro) averaging.
In Manning's Introduction to Information Retrieval (pg. 260) they show
it is possible to obtain it.(In fact I modified this line, in
metrics.py, and the value was indeed returned, after a macro averaging.)
I guess I am missing something, just want to be sure.
Pavel S.
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