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support for text features and multi-value category features and sequence features #174

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Lapis-Hong opened this issue Mar 1, 2023 · 3 comments

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@Lapis-Hong
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  1. text features:
    use text encoder as an embedding input, can join with continuous feature to feed to existed models

  2. multi-value category features
    like [a, b, c], can process similar to categorical features, but with pooling to sum its embeddings

  3. sequence features
    like [s1,s2,...sn], can use embedding an attention

@manujosephv
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I feel these are more nuanced use-cases and form the question, I assume you are trying to sue this for recommendation systems?

PyTorch Tabular is more geared towards standard tabular problems like classification and regression. That is why multi-hot categorical features aren't supported out of the box.

Adding support for Text and Sequence Features is a good idea and I'm all for it. It should be easy enough to include and parametrize that. As things stand now, you can implement custom models to include such features..

@Lapis-Hong
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thanks, i am doing classification and regression probs, in real world big scale data, actually there always exists multi-value data, looking forward for text and sequence features support~

@stale
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stale bot commented May 5, 2023

This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.

@stale stale bot added the wontfix This will not be worked on label May 5, 2023
@manujosephv manujosephv added Open for Contribution and removed wontfix This will not be worked on labels May 6, 2023
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