原文出处:http://www.linuxdiyf.com/linux/23764.html
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.
XGBoost可在Windows、Linux、Mac OS X上使用,支持多种编程语言:C++, Python, R, Java, Scala, Julia等。
安装XGBoost-Python
安装基本开发工具:
$ sudo apt install git build-essential python-dev python-setuptools python-pip python-numpy python-scipy
从Github下载最新源代码:
$ git clone --recursive https://github.com/dmlc/xgboost
编译:
$ cd xgboost
$ make -j4
生成的库:lib/libxgboost.so、lib/libxgboost.a;命令行工具:xgboost。
安装Python包:
$ cd python-package/
$ sudo python setup.py install
# 或
# $ sudo python setup.py install --user
测试:

XGBoost是一款高效、灵活且可移植的梯度提升库,适用于大规模数据科学问题。它支持并行树提升,可在多种分布式环境中运行,并能处理数十亿级别的数据。XGBoost可在多个操作系统上使用,包括Windows、Linux和MacOSX,并支持多种编程语言如C++、Python、R等。本文介绍了如何在Linux环境下安装XGBoost及其Python包。
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