Mean Average Precision Metrics

I am working on multilabel classification and I would like to implement Mean Average Precision (MaP) metrics. I am trying to understand the idea. So far I have read on how precision works on binary classification. Any idea how can this be implemented?

I saw this thread trying to understand mAP, maybe it can help you out :slight_smile:
In particular in the first post there’s a few good links.

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Thanks for the link. There are good explanations which i have to read and try to understand.