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

Installers

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

conda install

  • linux-64  v1.4.2
  • osx-64  v1.4.2
  • win-64  v1.4.2
To install this package with conda run one of the following:
conda install -c conda-forge xgboost
conda install -c conda-forge/label/gcc7 xgboost
conda install -c conda-forge/label/cf201901 xgboost
conda install -c conda-forge/label/cf202003 xgboost

Description

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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