Tensorflow-decision-forests

Features

- Added support for Python 3.12.
- New hyperparameters for configuring sparse oblique splits:
`sparse_oblique_max_num_features`, `sparse_oblique_weights_integer_maximum`,`sparse_oblique_weights_integer_minimum`,
`sparse_oblique_weights_power_of_two_max_exponent`, `sparse_oblique_weights_power_of_two_min_exponent`.

Fix

- Fix compatibility with TF 2.19.0.
- Fix handling of categorical variables with non-unicode values.
- Fix compatibility with new YDF models.
- Various documentation improvements.

Feature

- Renamed LAMBDA_MART_NDCG5 loss to LAMBDA_MART_NDCG. The old loss is still
available. The ndcg truncation can now be modified via a hyperparameter.
- Notify users about ydf during startup. This message can be disabled by
setting Environment variable TFDF_DISABLE_WELCOME_MESSAGE.

Fix

- Some errors are now InvalidArgumentError instead of UnknownError.
- Fix compatibility with TF 2.18.0.

Fix

- Fix compatibility with TF 2.17.0.
- Fix MacOS build.

Fix

- Fix compatibility with TF 2.16.2.
- Fix build.

Fix

- Solve dependency collision of YDF Proto between PYDF and TF-DF.

Fix

- Fix max_depth, early stopping parameter documentation.
- Fix plotting contains conditions.

Features

- Compatibility with TensorFlow 2.16.0rc0.
- Expose new parameter sparse_oblique_max_num_projections.
- Using tf_keras instead tf.keras in examples, documentation.
- Support NAConditions for fast engine.
- Faster model loading for models with many features and dense oblique
conditions.

Documentation

- Clarified documentation of parameters for oblique splits.