## 0.9.0 (2024-10-17) - Updated XGBoost to 2.1.1 - Added support for callbacks - Added `num_features` and `save_config` methods to `Booster` - Added `num_nonmissing` and `data_split_mode` methods to `DMatrix` - Dropped support for Ruby < 3.1 ## 0.8.0 (2023-09-13) - Updated XGBoost to 2.0.0 - Dropped support for Ruby < 3 ## 0.7.3 (2023-07-24) - Fixed error with `dup` and `clone` ## 0.7.2 (2023-05-12) - Updated XGBoost to 1.7.5 - Added musl shared library for Linux - Improved error message for invalid matrix ## 0.7.1 (2022-10-31) - Updated XGBoost to 1.7.0 ## 0.7.0 (2022-06-05) - Updated XGBoost to 1.6.1 - Improved ARM detection - Dropped support for Ruby < 2.7 ## 0.6.0 (2021-10-23) - Updated XGBoost to 1.5.0 ## 0.5.3 (2021-05-12) - Updated XGBoost to 1.4.0 - Added ARM shared library for Linux ## 0.5.2 (2021-03-09) - Added ARM shared library for Mac ## 0.5.1 (2021-02-08) - Fixed error with validation sets without early stopping ## 0.5.0 (2020-12-12) - Updated XGBoost to 1.3.0 ## 0.4.1 (2020-08-26) - Updated XGBoost to 1.2.0 ## 0.4.0 (2020-05-17) - Updated XGBoost to 1.1.0 - Changed default `learning_rate` and `max_depth` for Scikit-Learn API to match Python - Added support for Rover - Improved performance of Numo datasets - Improved error message when OpenMP not found on Mac ## 0.3.1 (2020-04-16) - Added `feature_names` and `feature_types` to `DMatrix` - Added feature names to `dump` ## 0.3.0 (2020-02-19) - Updated XGBoost to 1.0.0 ## 0.2.1 (2020-02-11) - Fixed `Could not find XGBoost` error on some Linux platforms - Fixed `SignalException` on Windows ## 0.2.0 (2020-01-26) - Prefer `XGBoost` over `Xgb` - Changed to Apache 2.0 license to match XGBoost - Added shared libraries - Added support for booster attributes ## 0.1.3 (2019-10-27) - Added support for missing values - Fixed Daru training and prediction - Fixed error with JRuby ## 0.1.2 (2019-08-19) - Friendlier message when XGBoost not found - Free memory when objects are destroyed - Added `Ranker` - Added early stopping to Scikit-Learn API ## 0.1.1 (2019-08-16) - Added Scikit-Learn API - Added early stopping - Added `cv` method - Added support for Daru and Numo::NArray - Added many other methods - Fixed shape of multiclass predictions when loaded from file ## 0.1.0 (2019-08-15) - First release