使用 fork 功能将在后台会为你创建一个与该项目内容一样的同名项目，你可以在这个新项目里自由的修改内容。
建议只在有意向参与改进该项目时使用 fork 功能。
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 has been developed and used by a group of active community members. Your help is very valuable to make the package better for everyone.
© Contributors, 2016. Licensed under an Apache-2 license.