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v0.5.0 - 2021-11-18

This release adds support for Python 3.9 and updates dependencies to ensure compatibility with the rest of the SDV ecosystem, and upgrades to the latests RDT release.

Issues closed

  • Add support for Python 3.9 - Issue #177 by @pvk-developer
  • Add pip check to CI workflows - Issue #174 by @pvk-developer
  • Typo in CTGAN code - Issue #158 by @ori-katz100 and @fealho

v0.4.3 - 2021-07-12

Dependency upgrades to ensure compatibility with the rest of the SDV ecosystem.

v0.4.2 - 2021-04-27

In this release, the way in which the loss function of the TVAE model was computed has been fixed. In addition, the default value of the discriminator_decay has been changed to a more optimal value. Also some improvements to the tests were added.

Issues closed

  • TVAE: loss function - Issue #143 by @fealho and @DingfanChen
  • Set discriminator_decay to 1e-6 - Pull request #145 by @fealho
  • Adds unit tests - Pull requests #140 by @fealho

v0.4.1 - 2021-03-30

This release exposes all the hyperparameters which the user may find useful for both CTGAN and TVAE. Also TVAE can now be fitted on datasets that are shorter than the batch size and drops the last batch only if the data size is not divisible by the batch size.

Issues closed

  • TVAE: Adapt batch_size to data size - Issue #135 by @fealho and @csala
  • ValueError from validate_discre_columns with uniqueCombinationConstraint - Issue 133 by @fealho and @MLjungg

v0.4.0 - 2021-02-24

Maintenance relese to upgrade dependencies to ensure compatibility with the rest of the SDV libraries.

Also add a validation on the CTGAN condition_column and condition_value inputs.

Improvements

  • Validate condition_column and condition_value - Issue #124 by @fealho

v0.3.1 - 2021-01-27

Improvements

  • Check discrete_columns valid before fitting - Issue #35 by @fealho

Bugs fixed

  • ValueError: max() arg is an empty sequence - Issue #115 by @fealho

v0.3.0 - 2020-12-18

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!

Improvements

  • Add TVAE - Issue #111 by @fealho
  • Move log_frequency to __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

Bugs fixed

  • Fixed NaN != NaN counting bug. - Issue #100 by @fealho
  • Update dependencies and testing - Issue #90 by @csala

v0.2.2 - 2020-11-13

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!

Improvements

  • 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

Bugs fixed

  • Loss to nan - Issue #73 by @fealho
  • Swapped the sklearn utils testing import statement - Issue #53 by @lurosenb

v0.2.1 - 2020-01-27

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!

Issues Resolved:

  • 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

v0.2.0 - 2019-12-18

Reorganization of the project structure with a new Python API, new Command Line Interface and increased data format support.

Issues Resolved:

  • Reorganize the project structure - Issue #10 by @csala
  • Move epochs to the fit method - Issue #5 by @csala

v0.1.0 - 2019-11-07

First Release - NeurIPS 2019 Version.