Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow


Info: This package contains files in non-standard labels.

conda install

  • linux-64  v1.4.3
To install this package run one of the following:
conda install -c intel xgboost
conda install -c "intel/label/oneapibeta" xgboost
conda install -c "intel/label/validation" xgboost


LEGAL NOTICE: Use of this software package is subject to the software license agreement (as set forth above, in the license section of the installed Conda package and/or the README file) and all notices, disclaimers or license terms for third party or open source software included in or with the software.

EULA: Apache-2.0

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.

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