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2 changes: 1 addition & 1 deletion doc/examples/warp_loss.rst
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Expand Up @@ -17,7 +17,7 @@ the form of the k-OS WARP loss, also implemented in LightFM.

Like the BPR model, WARP deals with (user, positive item, negative item)
triplets. Unlike BPR, the negative items in the triplet are not chosen
by random sampling: they are chosen from among those negatie items which
by random sampling: they are chosen from among those negative items which
would violate the desired item ranking given the state of the model.
This approximates a form of active learning where the model selects
those triplets that it cannot currently rank correctly.
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