When using cross_val_score, one can choose an averaging method easily using the various scoring presets. But if they want to choose a pos_label like those taken by f1, precision, and recall (to specify scoring with respect to a specific class), they have to define a custom scoring function like this:

def precision_class_2(estimator, X, y):
    y_pred = estimator.predict(X)
    return metrics.precision(y, y_pred, pos_label=2)

cross_val_score(estimator, X, y=None, scoring=precision_class_2)

This obviously isn't that big of a deal, but it would be nice to be able to pass scoring parameters into the function the same way you can pass fit parameters. Like:

cross_val_score(estimator, X, y=None, scoring='precision', scoring_params={'pos_label':2})

I'm happy to contribute code for this but wanted to open an issue first and see what others think/if I'm barking up the wrong tree.