Brier Score

Problem

Compute the Brier score for binary probability predictions: (1/n) * sum((p_i - y_i)^2).

Empty input returns 0.0.

Hint

It is the mean squared error between predicted probabilities and 0/1 labels.

case 1

in: [[1,0,1,0],[0.9,0.1,0.8,0.2]]

expected: 0.024999999999999994

case 2

in: [[1,1],[0.5,0.5]]

expected: 0.25

case 3

in: [[0,0],[0,1]]

expected: 0.5

case 4

in: [[],[]]

expected: 0

Starter codePython

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

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