I gather there's a lot of historical default behaviour in those metrics.
This results in a few quirks some of which are real problems, as in
https://github.com/scikit-learn/scikit-learn/issues/2094. It should be
cleaned up, but existing behaviour will need to be maintained for at least
two releases. Feel free to do the cleaning and submit a PR.
- Joel
On Wed, Aug 7, 2013 at 10:19 PM, Bertrand Thirion <bertrand.thir...@inria.fr
> wrote:
> Dear all,
>
> In the sklearn.metrics module, the precision_recall_fscore_support and
> precision_score have different default value for the "average" parameter,
> which seems a bit counterintuitive -- but I did not go deep into the code.
> Is this really the intended behavior ?
>
> def precision_score(y_true, y_pred, labels=None, pos_label=1,
> average='weighted')
> def precision_recall_fscore_support(y_true, y_pred, beta=1.0, labels=None,
> pos_label=1, average=None)
>
> Best,
>
> Bertrand
>
>
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