Comments (3)
Hi there!
Just wanted to ask, whether this might be actually worthwhile feature for you folks (that might be even already on the update list) or something you wouldn't consider in near future.
Regards,
Tobias
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Hi @tolandwehr ,
I think this feature is related to synthesizing a database. In a database, there are multiple tables. In your example, there are some two tables. One contains (object_id, static_features), and the other contains (object_id, year_id, dynamic features). The latter one also requires the capability of generating time-series data. I would not consider adding this feature to CTGAN project in the near feature. But we do have some a related project SDV. SDV can generate tables with hierarchical structure.
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Closing this as, like @leix28 said, this is being worked on in the related project SDV Don't forget to check it out!
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Related Issues (20)
- TypeError while ctgan.fit() HOT 6
- Improve DataSampler efficiency
- ValueError: mismatch of shapes when sampling data for compas dataset HOT 2
- Return loss values as float values not PyTorch objects
- Transition from using setup.py to pyproject.toml to specify project metadata
- Remove bumpversion and use bump-my-version
- Switch to using ruff for Python linting and code formatting
- Add dependency checker
- Remove scikit-learn dependency
- CTGAN using deprecated 'sklearn' HOT 2
- Replace integration test that uses the iris demo data
- Add bandit workflow
- Feature Request: More verbose logging HOT 3
- Fix minimum version workflow when pointing to github branch
- Deployment requirements based on libtorch or ONNX HOT 4
- How to load this model directly to generate data after saving it HOT 4
- Cleanup automated PR workflows
- Remove FutureWarning: Setting an item of incompatible dtype is deprecated
- Only run unit and integration tests on oldest and latest python versions for macos
- [HELP] CTGAN has Reproducibility? HOT 8
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