tabnet 0.3.0
- Added an
update method for tabnet models to allow the correct usage of finalize_workflow (#60).
tabnet 0.2.0
New features
- Allow model fine-tuning through passing a pre-trained model to
tabnet_fit() (@cregouby, #26)
- Explicit error in case of missing values (@cregouby, #24)
- Better handling of larger datasets when running
tabnet_explain().
- Add
tabnet_pretrain() for unsupervised pretraining (@cregouby, #29)
- Add
autoplot() of model loss among epochs (@cregouby, #36)
- Added a
config argument to fit() / pretrain() so one can pass a pre-made config list. (#42)
- In
tabnet_config(), new mask_type option with entmax additional to default sparsemax (@cmcmaster1, #48)
- In
tabnet_config(), loss now also takes function (@cregouby, #55)
Bugfixes
- Fixed bug in GPU training. (#22)
- Fixed memory leaks when using custom autograd function.
- Batch predictions to avoid OOM error.
Internal improvements
tabnet 0.1.0
- Added a
NEWS.md file to track changes to the package.