0

Minimum Margin

Unsolved
Active Learning

Difficulty: 4 | Problem written by peter.washington
Problem reported in interviews at     The minimum margin of the output probability distribution (the difference between the largest probability in the distribution and the second highest probability in the distributtion) is a common metric for active learning. In each test case for this problem, you will be given a list of numpy arrays representing probability distributions. Your job is to calculate the index of the probability distribution with the minimum margin. (If the first numpy array represents the distribution with the minimum margin, then return 0; if the second numpy array represents the distribution with the minimum margin, then return 1; etc).

Sample Input:
<class 'list'>
probability_distributions: [array([0.1 , 0.5 , 0.1 , 0.15, 0.15]), array([0.2, 0.2, 0.2, 0.2, 0.2])]

Expected Output:
<class 'int'>
1

MLPro Premium also allows you to access all our high quality MCQs which are not available on the free tier.

Not able to solve a problem? MLPro premium brings you access to solutions for all problems available on MLPro

Have an issue, the MLPro support team is available 24X7 to Premium users.