CodingMediumcod-g984

Subject Ml metricsLevel Mid–Senior~18 minCommon in ML systems interviewsIndustries Software development, Technology

Question

Compute the Shannon entropy (in bits, base-2) of a list of class labels. Entropy = -sum over each class of p * log2(p), where p is the class's fraction. By convention a class contributing p = 0 adds nothing, and a pure single-class list has entropy 0. The input list is non-empty. Round the result to 6 decimal places.

Implement

entropy(labels: list[str]) → float

Examples

in[["a","a","b","b"]]out1

What a strong answer looks like

State your approach and its time/space complexity out loud before you optimize. Handle the edge cases (empty input, duplicates, overflow), and say why you chose this over the brute force. Green tests are the floor, not the grade.

Learn the concepts

Vibe coding: describe the solution in plain language (or narrate it) and the coach grades your approach. Generating runnable code from your description is coming next.

Run or narrate your approach, then ask the coach.