DOC Fixing language in Hamming loss docstring.
@@ -1993,7 +1993,7 @@ def hamming_loss(y_true, y_pred, labels=None, sample_weight=None):
In multilabel classification, the Hamming loss is different from the
subset zero-one loss. The zero-one loss considers the entire set of labels
- for a given sample incorrect if it does entirely match the true set of
+ for a given sample incorrect if it does not entirely match the true set of
labels. Hamming loss is more forgiving in that it penalizes the individual
labels.
