【机器学习】 之 xgboost python ubuntu部署

安装XGBoost-Python

pip install xgboost --index https://pypi.mirrors.ustc.edu.cn/simple/

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：

1	$ git clone -- recursive https : / / github .com / dmlc / xgboost

编译：

1 2	$ cd xgboost $ make - j4

生成的库：lib/libxgboost.so、lib/libxgboost.a；命令行工具：xgboost。

安装Python包：

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$ cd python - package / $ sudo python setup .py install # 或 # $ sudo python setup.py install --user

测试：

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import xgboost as xgb # read in data dtrain = xgb . DMatrix ( 'demo/data/agaricus.txt.train' ) dtest = xgb . DMatrix ( 'demo/data/agaricus.txt.test' ) # specify parameters via map param = { 'max_depth' : 2 , 'eta' : 1 , 'silent' : 1 , 'objective' : 'binary:logistic' } num_round = 2 bst = xgb . train ( param , dtrain , num_round ) # make prediction preds = bst . predict ( dtest )

安装XGBoost-R

安装XGBoost包：

1 2	> install . packages ( 'xgboost' ) > library ( xgboost )

测试：

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# load data data ( agaricus . train , package = 'xgboost' ) data ( agaricus . test , package = 'xgboost' ) train < - agaricus . train test < - agaricus . test # fit model bst < - xgboost ( data = train $ data , label = train $ label , max . depth = 2 , eta = 1 , nround = 2 , nthread = 2 , objective = "binary:logistic" ) # predict pred < - predict ( bst , test $ data )

• XGBoost源代码：https://github.com/dmlc/xgboost
• XGBoost的文档：http://xgboost.readthedocs.io/en/latest/