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We typically use the retrieval model to narrow the set of candidates to maybe 10 or 100 before ranking them with the ranking model, so yes, you can probably skip the retrieval stage.
Hi, my training data involves implicit feedback from users, specifically their past purchase history (no ratings).
Our item catalog is small, around 20 items. The goal is to rank these items based on the probability of users making a purchase.
Considering the limited item size, I'm thinking of skipping the retrieval model and using a ranking model directly. Is this the right approach?
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