[ASK] Sequential Recommender (SLi_Rec) Questions
#1040 aperta il 22 gen 2020
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When we create a dataset for the predict function in SLi_Rec do we need to start with a label i.e. 1 or 0 and what timestamp should we use? If we use a future timestamp does the model provide a probability based on the timestamp? How about if we use the timestamp for NOW() or a timestamp in the past?
What are the tradeoffs/benefits for min_sequence_len and max_sequence_len in terms of network complexity and compute memory and time?
Is there a way to influence the alpha parameter that balances short-term and long-term?
What were the RAM requirements for the full Amazon dataset and the training data file size?
Any tips on providing the model with a more complex representation for Category. I see that under the hood there is an embedding happening, wondering if there is a way to include a combination of columns.