diff --git a/sklearn/multioutput.py b/sklearn/multioutput.py
index 64e394272ffd7fd9211d2d356a0ebd597cad0f2d..6906d95869f2bfe7eeecfc9b9ba0e26d413fce52 100644
--- a/sklearn/multioutput.py
+++ b/sklearn/multioutput.py
@@ -252,8 +252,8 @@ class MultiOutputRegressor(MultiOutputEstimator, RegressorMixin):
     def score(self, X, y, sample_weight=None):
         """Returns the coefficient of determination R^2 of the prediction.
 
-        The coefficient R^2 is defined as (1 - u/v), where u is the regression
-        sum of squares ((y_true - y_pred) ** 2).sum() and v is the residual
+        The coefficient R^2 is defined as (1 - u/v), where u is the residual
+        sum of squares ((y_true - y_pred) ** 2).sum() and v is the regression
         sum of squares ((y_true - y_true.mean()) ** 2).sum().
         Best possible score is 1.0 and it can be negative (because the
         model can be arbitrarily worse). A constant model that always