One Ranking, Four Metrics

Four metrics, four different questions about ranking quality. Pick the wrong one and you optimize for the wrong behavior.

Precision@K asks how many of the top K results are relevant. It matters when every result on screen carries equal weight, like a recommendation grid or a product carousel.

Recall@K asks how many of all the relevant items made it into the top K. It matters when completeness is the whole point: legal discovery, medical search, compliance audits.

MRR asks where the first relevant result shows up. It matters when people only look at the top hit. Voice assistants, autocomplete, "I'm feeling lucky."

NDCG rewards relevant results near the top and discounts them as they sink down the page. It matters when users scan a full page of results. Web search, document retrieval, any ranked feed.

The part most people miss is that these metrics disagree. A system with perfect MRR can have terrible recall. A system with great recall can score low on NDCG if all the relevant items sit at the bottom.

Pick the metric that matches how your users actually behave. Anything else is just measuring to fill a dashboard.