In this release we add a new TVAE model which was presented in the original CTGAN paper. It also exposes more hyperparameters and moves epochs and log_frequency from fit to the constructor.
A new verbose argument has been added to optionally disable unnecessary printing, and a new hyperparameter
called discriminator_steps has been added to CTGAN to control the number of optimization steps performed
in the discriminator for each generator epoch.
The code has also been reorganized and cleaned up for better readability and interpretability.
Special thanks to @Baukebrenninkmeijer @fealho @leix28 @csala for the contributions!
- Add TVAE - Issue #111 by @fealho
- Move
log_frequencyto__init__- Issue #102 by @fealho - Add discriminator steps hyperparameter - Issue #101 by @Baukebrenninkmeijer
- Code cleanup / Expose hyperparameters - Issue #59 by @fealho and @leix28
- Publish to conda repo - Issue #54 by @fealho
- Fixed NaN != NaN counting bug. - Issue #100 by @fealho
- Update dependencies and testing - Issue #90 by @csala
In this release we introduce several minor improvements to make CTGAN more versatile and propertly support new types of data, such as categorical NaN values, as well as conditional sampling and features to save and load models.
Additionally, the dependency ranges and python versions have been updated to support up to date runtimes.
Many thanks @fealho @leix28 @csala @oregonpillow and @lurosenb for working on making this release possible!
- Drop Python 3.5 support - Issue #79 by @fealho
- Support NaN values in categorical variables - Issue #78 by @fealho
- Sample synthetic data conditioning on a discrete column - Issue #69 by @leix28
- Support recent versions of pandas - Issue #57 by @csala
- Easy solution for restoring original dtypes - Issue #26 by @oregonpillow
- Loss to nan - Issue #73 by @fealho
- Swapped the sklearn utils testing import statement - Issue #53 by @lurosenb
Minor version including changes to ensure the logs are properly printed and the option to disable the log transformation to the discrete column frequencies.
Special thanks to @kevinykuo for the contributions!
- Option to sample from true data frequency instead of logged frequency - Issue #16 by @kevinykuo
- Flush stdout buffer for epoch updates - Issue #14 by @kevinykuo
Reorganization of the project structure with a new Python API, new Command Line Interface and increased data format support.
- Reorganize the project structure - Issue #10 by @csala
- Move epochs to the fit method - Issue #5 by @csala
First Release - NeurIPS 2019 Version.