AI engineering glossary · Evaluation metrics
What is MAP (mean average precision)?
Mean average precision (also called MAP): For each query, the average precision is the mean of the precision values at the rank of every relevant result; MAP is that figure averaged across queries. It rewards ranking relevant items early and covers the whole list, so it is a standard for search and retrieval systems.
Mean average precision: an example
For a query with 3 relevant items found at ranks 1, 3 and 5, the precisions are 1, 0.67 and 0.6, so AP is about 0.76. MAP averages such values over all queries.
Related terms
More Evaluation metrics terms
- Mean bias error
- Mean reciprocal rank
- Mean squared error
- Mean squared logarithmic error
- Median absolute error
- METEOR
- Micro averaging
- Negative predictive value
Where you learn it
Mean average precision is part of the AI Engineering Program, which teaches it with notes, a hands-on lab and an exam. The first lesson is free.