recommender_pytorch
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why convert to implicit scenario
wondering why the ratings are all set to 1 in the dataset as implicit scenario. Thanks!
In the implicit scenario, you are just deciding weather to recommend a movie or not, it becomes a binary problem. Hence you just use 0 or 1, instead of fine granular rating. This is mostly picked up from the literature on recommender systems, and is not something new for this model.
Thank you! Did not realize it was trying to simplify the number of classes.