DOC Residual sum vs. regression sum
@@ -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
