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."
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.