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From what I've read, F1-score is a commonly used metric to assess the performance of a multilabel classification problem.

However, I recently came across mAP@K and mAR@K as metrics used for recommender systems/information retrieval systems. These values help in judging the model based on the top K items recommended by the system and change as the value of K changes.

I am interested in understanding if mAP@K and mAR@K are valid metrics for a simple multilabel classification problem. I'm aware that in multilabel classification, there is no concept of "retrieving the top K" predictions but I would like to know if my understanding is correct.

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