Root Mean Squared Error for Regression

Problem

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

Empty input returns 0.0.

Hint

Take the square root of the MSE.

case 1

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

expected: 0

case 2

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

expected: 3.5355339059327378

case 3

in: [[2,4,6],[1,2,3]]

expected: 2.160246899469287

case 4

in: [[],[]]

expected: 0

Starter codePython

import math
def root_mean_squared_error(y_true, y_pred):
    # Your code here
    pass

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