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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 01:02:12 2025
md5 checksum cb4b5eea14c00cd31ce3955a2dd522ea
arch x86_64
build py312h06a4308_0
depends _py-xgboost-mutex 2.0 cpu_0, libxgboost 1.7.6 h6a678d5_0, numpy <2.0a0, python >=3.12,<3.13.0a0, scikit-learn, scipy
license Apache-2.0
license_family Apache
md5 cb4b5eea14c00cd31ce3955a2dd522ea
name py-xgboost
platform linux
sha1 2e4e84ed4fe5510ec2ffc767fcb1b3785cc59406
sha256 6bd69b6d5d5ca51e299541121a602b4f803e37b4afd3af10fef1de6a4d4dc54d
size 295051
subdir linux-64
timestamp 1712794900680
version 1.7.6