Save predictions in diabetes_y_pred

davidrobles · davidrobles · commit 13d9d6e2c60a · 2017-01-28T07:36:37.000-08:00
No need for `regr.predict(diabetes_X_test)` to run twice.
diff --git a/examples/linear_model/plot_ols.py b/examples/linear_model/plot_ols.py
@@ -48,18 +48,20 @@
 # Train the model using the training sets
 regr.fit(diabetes_X_train, diabetes_y_train)
 
+# Make predictions using the testing set
+diabetes_y_pred = regr.predict(diabetes_X_test)
+
 # The coefficients
 print('Coefficients: \n', regr.coef_)
 # The mean squared error
 print("Mean squared error: %.2f"
-      % np.mean((regr.predict(diabetes_X_test) - diabetes_y_test) ** 2))
+      % np.mean((diabetes_y_pred - diabetes_y_test) ** 2))
 # Explained variance score: 1 is perfect prediction
 print('Variance score: %.2f' % regr.score(diabetes_X_test, diabetes_y_test))
 
 # Plot outputs
 plt.scatter(diabetes_X_test, diabetes_y_test,  color='black')
-plt.plot(diabetes_X_test, regr.predict(diabetes_X_test), color='blue',
-         linewidth=3)
+plt.plot(diabetes_X_test, diabetes_y_pred, color='blue', linewidth=3)
 
 plt.xticks(())
 plt.yticks(())
