How to Evaluate Retrieval Quality in RAG Pipelines (part 2): Mean Reciprocal Rank (MRR) and Average Precision (AP)
NeutralArtificial Intelligence
How to Evaluate Retrieval Quality in RAG Pipelines (part 2): Mean Reciprocal Rank (MRR) and Average Precision (AP)
The article discusses methods for evaluating the retrieval quality of RAG pipelines, focusing on metrics like Mean Reciprocal Rank (MRR) and Average Precision (AP). Understanding these evaluation techniques is crucial for improving data retrieval systems, ensuring that users receive the most relevant information efficiently. This knowledge is particularly valuable for data scientists and engineers working on enhancing machine learning models.
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