Merge pull request scikit-learn#5954 from KjellSwedin/correct_LinearRegression_example

residual sum of squares should be computed by summing the squared dif…

Author: agramfort

examples/linear_model/plot_ols.py

@@ -50,8 +50,8 @@
 
 # The coefficients
 print('Coefficients: \n', regr.coef_)
-# The mean square error
-print("Residual sum of squares: %.2f"
+# The mean squared error
+print("Mean squared error: %.2f"
       % np.mean((regr.predict(diabetes_X_test) - diabetes_y_test) ** 2))
 # Explained variance score: 1 is perfect prediction
 print('Variance score: %.2f' % regr.score(diabetes_X_test, diabetes_y_test))