Mean Absolute Error for Regression

Problem

Compute the mean absolute error: MAE = (1/n) * sum(|y_true_i - y_pred_i|).

Empty input returns 0.0.

Hint

Average the absolute residuals.

case 1

in: [[1,2,3,4],[1,2,3,4]]

expected: 0

case 2

in: [[1,2,3],[2,4,1]]

expected: 1.6666666666666667

case 3

in: [[-1,-2],[1,2]]

expected: 3

case 4

in: [[],[]]

expected: 0

Starter codePython

def mean_absolute_error(y_true, y_pred):
    # Your code here
    pass

4 test cases · run your code against them in the editor