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embedding of categorical variables #37
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Hi @lhq12 , pretraining is not needed. The embedding layer is just a module, so it should be a part of the model and should be trained with the model. Could you clarify, please, is your question related to the |
Yes, this is related to "Revisiting Deep Learning Models for Tabular Data". I am confused about the details of embedding categorical features, that is why I am here reading rtdl. I still have a question, without pretraining, embeddings of those categories unseen at training stage are just random noises. Are there any tricks to handle this or we don't care about this? |
This is an important detail :) I can think of several possible strategies, it depends on your specific problem what will work better:
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Hi Yury,
Thank you for your excellent work. I get a problem when handling categorical features. Do I need to pre-train the embedding layer when applying it to the data processing or just to attach the embedding layer to the model and train it with the model.
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