Definition
Mean Average Precision (MAP) is a ranking metric that evaluates a retriever's ability to place relevant documents at the top of a result set by averaging the precision at each relevant document's rank across multiple queries. While it ensures high-quality context for the LLM, optimizing for MAP often requires a trade-off between retrieval latency and accuracy, typically necessitating computationally expensive re-ranking stages.
A search evaluation metric for ranking, not a geographic map or a data transformation function.
"A grocery store shelf where the freshest, most relevant ingredients for your specific recipe are placed exactly at eye level, rather than hidden on the bottom shelf."
- Precision@K(Component)
- MRR (Mean Reciprocal Rank)(Alternative Metric)
- Recall(Prerequisite)
- Re-ranking(Optimization Technique)
Conceptual Overview
Mean Average Precision (MAP) is a ranking metric that evaluates a retriever's ability to place relevant documents at the top of a result set by averaging the precision at each relevant document's rank across multiple queries. While it ensures high-quality context for the LLM, optimizing for MAP often requires a trade-off between retrieval latency and accuracy, typically necessitating computationally expensive re-ranking stages.
Disambiguation
A search evaluation metric for ranking, not a geographic map or a data transformation function.
Visual Analog
A grocery store shelf where the freshest, most relevant ingredients for your specific recipe are placed exactly at eye level, rather than hidden on the bottom shelf.