DOC: complete docstring for regression score function

Fabian Pedregosa · Fabian Pedregosa · commit 9d638ec41ef7 · 2012-01-10T15:13:35.000+01:00
diff --git a/sklearn/base.py b/sklearn/base.py
@@ -273,7 +273,13 @@ class RegressorMixin(object):
     """Mixin class for all regression estimators in scikit-learn"""
 
     def score(self, X, y):
-        """Returns the coefficient of determination of the prediction
+        """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 - y_pred) ** 2).sum() and v is the
+        residual sum of squares ((y_true - y_true.mean()) ** 2).sum().
+        Best possible score is 1.0, lower values are worse.
+
 
         Parameters
         ----------
diff --git a/sklearn/metrics/metrics.py b/sklearn/metrics/metrics.py
@@ -624,16 +624,20 @@ def r2_score(y_true, y_pred):
 
     Best possible score is 1.0, lower values are worse.
 
-    Note: not a symmetric function.
-
-    return the R^2 score
-
     Parameters
     ----------
     y_true : array-like
 
     y_pred : array-like
 
+    Returns
+    -------
+    z : float
+        The R^2 score
+
+    Notes
+    -----
+    This is not a symmetric function.
     """
     y_true, y_pred = check_arrays(y_true, y_pred)
     numerator = ((y_true - y_pred) ** 2).sum()
