Mean Squared Error

Problem

Compute the mean squared error: MSE = (1/n) * sum((y_true_i - y_pred_i)^2).

Empty input returns 0.0.

Hint

Average the squared residuals.

case 1

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

expected: 0

case 2

in: [[1,2,3],[1,2,5]]

expected: 1.3333333333333333

case 3

in: [[0,0],[3,4]]

expected: 12.5

case 4

in: [[],[]]

expected: 0

Starter codePython

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

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