Mean absolute error

Communicating modeling results can be difficult. However, most clients understand that on average, a predictive model was off by some number. This makes explaining the mean absolute error easy. For example, when predicting the number of wins for a basketball team, if you predict 42, and they end up with 40, you can easily explain that the error was two wins.

In this exercise, you are interviewing for a new position and are provided with two arrays. y_test, the true number of wins for all 30 NBA teams in 2017 and predictions, which contains a prediction for each team. To test your understanding, you are asked to both manually calculate the MAE and use sklearn.

Manually calculate the MAE using n as the number of observations predicted.
Calculate the MAE using sklearn.
Print off both accuracy values using the print statements.

Exercise

Mean absolute error

Instructions