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 01:02:14 2025 |
md5 checksum | 0b29c28ef923f5b992e7aba587049852 |
arch | x86_64 |
build | py311h06a4308_0 |
depends | _py-xgboost-mutex 2.0 cpu_0, libxgboost 1.7.3 h6a678d5_0, numpy <2.0a0, python >=3.11,<3.12.0a0, scikit-learn, scipy |
license | Apache-2.0 |
license_family | Apache |
md5 | 0b29c28ef923f5b992e7aba587049852 |
name | py-xgboost |
platform | linux |
sha1 | 0f754581b545f364f46c26301fef348b7459c4e3 |
sha256 | af7a09e377a5f1a67d7f28666eaf322d2c30dc6d8cc228ea8e388adfedbe3f9e |
size | 284872 |
subdir | linux-64 |
timestamp | 1676922101332 |
version | 1.7.3 |