Negative Predictive Value

Problem

Compute the negative predictive value: TN / (TN + FN), the share of negative predictions that are correct.

Return 0.0 when the denominator is zero or the input is empty.

Hint

It is precision applied to the negative class.

case 1

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

expected: 0.6666666666666666

case 2

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

expected: 1

case 3

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

expected: 0

case 4

in: [[],[]]

expected: 0

Starter codePython

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

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