Dynamicis renamed to
- Data visualisation functionality in Jupyter Notebook requires ipywidgets 7.x+ now.
query_idparameter renamed to
group_idin Python and R wrappers.
- cv returns pandas.DataFrame by default if Pandas installed. See new parameter
Major Features And Improvements
- CatBoost build with make file. Now it’s possible to build command-line CPU version of CatBoost under Linux with make file.
- In column description column name
Targetis changed to
Label. It will still work with previous name, but it is recommended to use the new one.
eval-metricsmode added into cmdline version. Metrics can be calculated for a given dataset using a previously trained model.
- New classification metric
- Load CatBoost model from memory. You can load your CatBoost model from file or initialize it from buffer in memory.
- Now you can run
fitfunction using file with dataset:
fit(train_path, eval_set=eval_path, column_description=cd_file). This will reduce memory consumption by up to two times.
- 12% speedup for training.
Bug Fixes and Other Changes
- JSON output data format is changed.
- Python whl binaries with CUDA 9.1 support for Linux OS published into the release assets.
Thanks to our Contributors
This release contains contributions from newbfg and CatBoost team.
We are grateful to all who filed issues or helped resolve them, asked and answered questions.