Type I and Type II Error Rates from Counts

Problem

Return [alpha, beta] from counts: alpha = fp/(fp+tn) is the false positive rate and beta = fn/(fn+tp) is the false negative rate. Return 0.0 for a ratio whose denominator is zero.

Hint

Alpha conditions on the true negatives and beta on the true positives.

Test cases

case 1

in: [90,10,10,90]

expected: [0.1,0.1]

case 2

in: [50,0,5,45]

expected: [0,0.09090909090909091]

case 3

in: [40,10,0,50]

expected: [0.16666666666666666,0]

case 4

in: [0,0,0,0]

expected: [0,0]

case 5

in: [80,20,20,80]

expected: [0.2,0.2]

Starter codePython

def type_error_rates(tp, fp, fn, tn):
    # Your code here
    pass

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