Mean Average Precision (mAP) is a metric used to evaluate the performance of models, particularly in information retrieval and object detection tasks. It combines the concepts of precision and recall by calculating the average precision across multiple queries or classes, thus providing a single score that reflects both the relevance of the retrieved items and the order in which they are retrieved. This metric is crucial for assessing how well recommender systems are performing, as it directly relates to their ability to suggest relevant items to users.
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