I think I should just merge this PR with #2676 which focuses on that
specifically. It doesn't entirely make sense without it.


On 19 January 2014 02:22, Gael Varoquaux <notifications@github.com> wrote:

>  In benchmarks/bench_multilabel_metrics.py:
>
> > @@ -20,7 +20,7 @@
> >
> >
> >  METRICS = {
> > -    'f1': f1_score,
> > +    'f1': partial(f1_score, average='micro'),
>
> I think that the docs (the part that describes the different scoring
> options
> http://scikit-learn.org/dev/modules/model_evaluation.html#common-cases-predefined-values) should be updated to stress this.
>
> —
> Reply to this email directly or view it on GitHub<https://github.com/scikit-learn/scikit-learn/pull/2679/files#r8988047>
> .
>