XGBoost is an optimized distributed gradient boosting library designed to be highly efficient, flexible and portable. It implements machine learning algorithms under the Gradient Boosting framework. XGBoost provides a parallel tree boosting (also known as GBDT, GBM) that solve many data science problems in a fast and accurate way. The same code runs on major distributed environment (Hadoop, SGE, MPI) and can solve problems beyond billions of examples.
| Uploaded | Mon Mar 31 01:02:26 2025 |
| md5 checksum | 42c2c0a23fecdd6c5d33ae1f0a60c1e8 |
| arch | x86_64 |
| build | py310h06a4308_2 |
| build_number | 2 |
| depends | _py-xgboost-mutex 2.0 cpu_0, libxgboost 1.5.0 h6a678d5_2, numpy <2.0a0, python >=3.10,<3.11.0a0, scikit-learn, scipy, setuptools |
| license | Apache-2.0 |
| md5 | 42c2c0a23fecdd6c5d33ae1f0a60c1e8 |
| name | py-xgboost |
| platform | linux |
| sha1 | 54cc6546ad0cbf0ebdf1082d12c08f865633f7df |
| sha256 | 5904f56641520ce65ab8c5aeeeb3c566840848602360f477c067c8d48ee5c81b |
| size | 159311 |
| subdir | linux-64 |
| timestamp | 1659549314254 |
| version | 1.5.0 |