Exercise

Visualize the results

We've fit our model with the custom loss function, and it's time to see how it is performing. We'll check the R\(^2\) values again with sklearn's r2_score() function, and we'll create a scatter plot of predictions versus actual values with plt.scatter(). This will yield some interesting results!

Instructions

100 XP

Create predictions on the test set with .predict(), model_2, and scaled_test_features.
Evaluate the R\(^2\) score on the test set predictions using test_preds and test_targets.
Plot the test set targets vs actual values with plt.scatter(), and label it 'test'.