Gini Impurity of Labels

Problem

Compute the Gini impurity of a list of labels, defined as 1 - sum(p_i^2) where p_i is the empirical frequency of each distinct label. Return 0.0 for an empty list.

Hint

Count each label, square the frequencies, and subtract from one.

Test cases

case 1

in: [["a","b"]]

expected: 0.5

case 2

in: [["a","a","b","b"]]

expected: 0.5

case 3

in: [["a","a","a"]]

expected: 0

case 4

in: [[]]

expected: 0

case 5

in: [["a","b","c","c"]]

expected: 0.625

Starter codePython

def gini_impurity(labels):
    # Your code here
    pass

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