from the official documentation link
In our training data we have positive (user, movie) pairs. To figure out how good our model is, we need to compare the affinity score that the model calculates for this pair to the scores of all the other possible candidates: if the score for the positive pair is higher than for all other candidates, our model is highly accurate.
how can they say the score for the positive pair should be higher than all other candidates , what happens if the positive pair has less ratings than the other positive pairs
can someone define the exact loss function here ?
what is compared with what
here
This means that every movie a user watched is a positive example, and every movie they have not seen is an implicit negative example
