Aghiles

Hi, thanks for this suggestion. - Could you please clarify what is the connection between the UIRT format and the SLRC method? - How does SLRC work, and how does...

Hi, thanks for raising this question. Ideally items that a given user has interacted with should be ignored (filtered out from the ranking list) if we wish not recommend them....

Hi @georgeguo-cn, ``rank_eval()`` already makes predictions for held out test items only: ```Python (u_indices, i_indices, r_values) = test_set.uir_tuple r_preds = np.fromiter( tqdm( ( model.rate(user_idx, item_idx).item() for user_idx, item_idx in zip(u_indices,...

> ### Description > Good afternoon! Help, please, to understand. If I trained the model on the data. And I need to predict, based on past data, a recommendation for...

> Hi! I am facing a similar issue while trying to employ a [User Split strategy](https://www.sciencedirect.com/science/article/pii/S0306457321001540?ref=cra_js_challenge&fr=RR-1) for train/val/test split. > > This means that instead of having, say of 60%...