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.