Comments (1)
Still, what does preprocess_user_item_features
do? Just enlarge the feature matrix with 0s. Any benefit for this strategy?
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Related Issues (16)
- error: Could not find suitable distribution for Requirement.parse('cPickle') HOT 1
- the W_user or W_movies HOT 1
- Adding side features to train_mini_batch.py
- Where is the augmented adjacency matrix in `global_normalize_bipartite_adjacency`
- How to apply multiple layers for the mini-batch version?
- I would like to ask about the "u_features" in the code.
- I would like to ask how to get the complete rating matrix predicted
- Questions On feed_dict
- Data's problem HOT 1
- Are you using test rating matrix during matrix completion?? HOT 1
- When running your code, some error happened HOT 1
- dropoutの追加 HOT 1
- weight initializationの追加 HOT 1
- datasetの作成 HOT 1
- test data generated from training data?
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