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From the paper "A Next Basket Recommendation Reality Check" in section 5.4 called "The relative contribution of repetition and exploration" metrics like recall or ndcg are separated into explore and repeat version of these, giving insight in how much the model performance comes from item that were already purchased before, or item that were never purchased before by a given user
This currently work only for sequential models, as I'm not experienced in modifying libraries, i decided to focus on parts I needed for my study