Regression evaluation
Let's revisit the linear regression model that you created with LinearRegression() and then trained with the fit() function a few exercises ago. Evaluate the performance your model, imported here as lm for you to call.
The weather data has been imported for you with the X and y variables as well, just like before. Let's get to calculating the R-squared, mean squared error, and mean absolute error values for the model.
This exercise is part of the course
Practicing Statistics Interview Questions in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# R-squared score
r2 = ____
print(____)