Comments (2)
In other words, the forward is like rnn, while the backward is like Markov model.
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If you are referring the lack of BPTT, check out issue #22 and the updated readme. The tl;dr version is that it doesn't improve performance on real life session data in experiments so was not included in the public version. Might be added later for folks working with longer sequences.
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Related Issues (20)
- About training time HOT 1
- Is it possible to output the embedding of user/session and item vectors? HOT 1
- Additional Negative Sampling: Conditional Statement Logic Error HOT 1
- generate_samples function call in gru4rec.py HOT 2
- BPR loss implementation question
- Fit function in gru4rec.py missing data sort HOT 1
- predict_next_batch not considering other products in the same session HOT 2
- (Question) - How to use all items in a session for prediction? HOT 2
- No hidden state reset in get_metrics HOT 4
- Where is the data file ?
- theano error HOT 2
- Can you make a brief explaination on how you calculate recall ? HOT 2
- Incremental training (retrain) support removed
- ValueError: Input dimension mis-match. (input[2].shape[0] = 2080, input[3].shape[0] = 32)
- cuda error
- GFF code
- Testing Error:: start = offset_sessions[iters] IndexError: index 2 is out of bounds for axis 0 with size 2
- Evaluating baselines
- Non-session based custom dataset HOT 2
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