FAQ: Multiple Linear Regression - Evaluating the Model's Accuracy

This community-built FAQ covers the “Evaluating the Model’s Accuracy” exercise from the lesson “Multiple Linear Regression”.

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This exercise can be found in the following Codecademy content:

Machine Learning

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Are we supposed to rely on the mean squared error regression loss for the testing set or the training set when evaluating the effectiveness of our model?

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Can anyone please explain how LinearRegression().score works?

How does it know which y-outputs to compare to calculate the R² coefficient?

In this exercise we provide (x_train, y_train) and (x_test, y_test) as inputs to obtain the mean squared error regression loss for the training set and the the testing set, respectively:

print(model.score(x_train, y_train))
print(model.score(x_test, y_test))

How does it know what the predicted y-values are?