Comments (2)
Of course you should use all training data for embedding layer. Generally, more data means more information, as long as you avoid to obtain information from test set.
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Thanks.
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Related Issues (20)
- Cannot reproduce meaningful embedding HOT 8
- Do you have any suggestions for network design? HOT 1
- Can't find the place where embedding pickle file is created HOT 1
- The embedding layer HOT 1
- delete thread
- Connecting embedding weights to a categorical value HOT 1
- Categorizations choice HOT 2
- Categorical Variables with long tail HOT 8
- Keras version problem HOT 7
- cannot reproduce "with EE" (with embeddings) paper results using this code HOT 4
- embedding results HOT 1
- Why not all features are used HOT 1
- Keras Reshape() layer HOT 1
- How to use the embedding on a new categorical data HOT 4
- Problem with Kaggle Branch
- CAN NOT FIND "embeddings.pickle" anywhere HOT 2
- when do u decide to dense or embed? HOT 5
- Lagged features HOT 4
- Can't pickle <class 'module'>: attribute lookup module on builtins failed HOT 3
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