nikrao opened a new pull request #7390: adding ranking metrics 
(precision/recall) at position K. 
   The file takes in data in dictionary format, for both predictions and ground 
   Ranking problems are very common in several areas of ML, and specifically 
computing metrics at a certain position is common in many applications. Usually 
for recommender systems, we don't want to compute the overall precision, but 
only, say precision@10, because only 10 items might be shown to the user. It 
makes sense to optimize your model that gets the top entries right, sacrificing 
overall precision. Similar arguments hold for recall, coverage etc. Having such 
a standard metric available in MXNet will let more people in the ML community 
make use of it, and increase it's adoptation. 
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