diff --git a/scikits/learn/linear_model/base.py b/scikits/learn/linear_model/base.py
index 4d3f08b41dd12405ecd7d0e1d8bdb4cdedf0d02c..7a4ba7f12be332dce282d568ef7ae1794eaa48f6 100644
--- a/scikits/learn/linear_model/base.py
+++ b/scikits/learn/linear_model/base.py
@@ -43,7 +43,7 @@ class LinearModel(BaseEstimator, RegressorMixin):
         X = np.asanyarray(X)
         return np.dot(X, self.coef_) + self.intercept_
 
-    def _explained_variance(self, X, y):
+    def _r2_score(self, X, y):
         """Compute explained variance a.k.a. r^2"""
         return r2_score(y, self.predict(X))
 
diff --git a/scikits/learn/linear_model/bayes.py b/scikits/learn/linear_model/bayes.py
index d040f52e7dda477c25e03b5c518a922223bcbf04..81e8c69ebcd9f9c973a30894e1f2d9f88d49f092 100644
--- a/scikits/learn/linear_model/bayes.py
+++ b/scikits/learn/linear_model/bayes.py
@@ -207,7 +207,7 @@ class BayesianRidge(LinearModel):
 
         self._set_intercept(Xmean, ymean)
         # Store explained variance for __str__
-        self.explained_variance_ = self._explained_variance(X, y)
+        self.r2_score_ = self._r2_score(X, y)
         return self
 
 
@@ -420,5 +420,5 @@ class ARDRegression(LinearModel):
 
         self._set_intercept(Xmean, ymean)
         # Store explained variance for __str__
-        self.explained_variance_ = self._explained_variance(X, y)
+        self.r2_score_ = self._r2_score(X, y)
         return self
diff --git a/scikits/learn/linear_model/coordinate_descent.py b/scikits/learn/linear_model/coordinate_descent.py
index dd9603cdf34afcb0a073f8e442a32fa445c03583..b16d74c14c769b494e5a0f739c37f93c8303c9e9 100644
--- a/scikits/learn/linear_model/coordinate_descent.py
+++ b/scikits/learn/linear_model/coordinate_descent.py
@@ -128,7 +128,7 @@ class ElasticNet(LinearModel):
                           ' to increase the number of interations')
 
         # Store explained variance for __str__
-        self.explained_variance_ = self._explained_variance(X, y) # XXX
+        self.r2_score_ = self._r2_score(X, y)
 
         # return self for chaining fit and predict calls
         return self
@@ -372,7 +372,7 @@ class LinearModelCV(LinearModel):
 
         self.coef_ = model.coef_
         self.intercept_ = model.intercept_
-        self.explained_variance_ = model.explained_variance_
+        self.r2_score_ = model.r2_score_
         self.alpha = model.alpha
         self.alphas = np.asarray(alphas)
         self.coef_path_ = np.asarray([model.coef_ for model in models])
diff --git a/scikits/learn/tests/test_metrics.py b/scikits/learn/tests/test_metrics.py
index eeb603bbe5ad8a850edc4de38f5c1442fc630b6d..f3c8896651d5c508ac54929819c1a821ae622b90 100644
--- a/scikits/learn/tests/test_metrics.py
+++ b/scikits/learn/tests/test_metrics.py
@@ -2,8 +2,6 @@ import random
 import numpy as np
 import nose
 
-# from numpy.testing import assert_
-# numpy.testing.assert_ only exists in recent versions of numpy
 from nose.tools import assert_true
 from numpy.testing import assert_array_almost_equal
 from numpy.testing import assert_array_equal