frozhen

Hello, have you found a solution to this issue that you could share? I'm wondering if it would make sense to treat the item/user feature weights are parameters and use...

I think there is a recall at k evaluation: https://making.lyst.com/lightfm/docs/lightfm.evaluation.html#lightfm.evaluation.recall_at_k , the link you shared seems to be the implicit package.

Did anyone have solutions for this issue yet? I'm facing the same problem where I have used historical interactions + user feature + item feature data to train a hybrid...

any updates? parsing values can be a pain if it's all nested and has different data types. This adds a lot of extra workload. If user simply passes in a...