Comments (1)
You can get the item embedding fairly simply. Depending on the value of the embedding
and constrained_embedding
model parameters, you can have have:
(a) only out item embedding in Wy
(embedding=0, constrained_embedding=False
)
(b) in and out item embeddings in E
and Wy
respectively (embedding=X, constrained_embedding=False
, X>0)
(c) unified item embedding in Wy
(embedding=0, constrained_embedding=True
)
Select the variable you want to get the embedding from and get its value from the theano shared variable (e.g. Wy.get_value(borrow=False)
). To match this to the item IDs in your data you must use the itemidmap
variable of the model (translates item IDs from your train data to indexes).
Getting session embeddings is not supported in the public version at the moment. This functionality might be added from the internal version in the future.
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Related Issues (20)
- About training time HOT 1
- NOT RNN MODEL HOT 2
- 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
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- Non-session based custom dataset HOT 2
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