Implements Multiclass hinge loss

Implements multiclass hinge loss. Fixes #3451 
Okay, I will leave this as it is for now.

On Mon, Sep 15, 2014 at 9:04 PM, Manoj Kumar <notifications@github.com>
wrote:

> In sklearn/metrics/classification.py:
>
> > @@ -1373,7 +1375,8 @@ def log_loss(y_true, y_pred, eps=1e-15, normalize=True, sample_weight=None):
> >      return _weighted_sum(loss, sample_weight, normalize)
> >
> >
> > -def hinge_loss(y_true, pred_decision, pos_label=None, neg_label=None):
> > +def hinge_loss(y_true, pred_decision, pos_label=None,
> > +               neg_label=None, labels=None):
> >      """Average hinge loss (non-regularized)
>
> git blame points me to @arjoly <https://github.com/arjoly> . Maybe he can
> confirm.
>
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> <https://github.com/scikit-learn/scikit-learn/pull/3607/files#r17548782>.
>