8000 [MRG+1] Residual sum vs. regression sum by SebastinSanty · Pull Request #9314 · scikit-learn/scikit-learn · GitHub
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[MRG+1] Residual sum vs. regression sum #9314

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Jul 10, 2017
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[MRG+1] Residual sum vs. regression sum #9314

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4 changes: 2 additions & 2 deletions sklearn/multioutput.py
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Expand Up @@ -252,8 +252,8 @@ def partial_fit(self, X, y, sample_weight=None):
def score(self, X, y, sample_weight=None):
"""Returns the coefficient of determination R^2 of the p 54F5 rediction.

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
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