Explained Sum of Squares

Problem

Compute the explained sum of squares of a regression: sum((pred_i - mean(y_true))^2).

Empty input returns 0.0.

Hint

Measure how far predictions spread around the mean of the true values.

case 1

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

expected: 2

case 2

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

expected: 0

case 3

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

expected: 3

case 4

in: [[],[]]

expected: 0

Starter codePython

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

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