Mean Average Precision

Task

Implement mean_average_precision(labels: list[int], scores: list[float]) -> float. Rank binary relevance labels by descending score, compute precision at every relevant result, and return the mean of those precision values.

Requirements

• Labels are binary, where 1 means relevant.
• Preserve original input order when scores tie.
• For every relevant item in ranked order, compute precision through that item's rank.
• Return the average of those relevant-item precision values.
• Return 0.0 when there are no relevant examples or when the input is empty.
• Do not apply a cutoff; evaluate the full ranked list.

Example

labels = [1, 0, 1, 1]
scores = [0.9, 0.8, 0.7, 0.6]

mean_average_precision(labels, scores)
# 0.8055555556