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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 01:02:14 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