XGBoost With Python Discover The Algorithm That Is Winning Machine Learning Competitions

xgboost是C++开源分布式机器学习系统DMLC的Boosting模型，单机采用多线程来加速树的构建，并依赖DMLC的另一个部件rabbit来进行分布式计算。xgboost提供了 Python和R语言接口。本文档由参与贡献的王超和陈帅华撰写。

This book is your guide to fast gradient boosting in Python. You will discover the XGBoost Python library for gradient boosting and how to use it to develop and evaluate gradient boosting models. In this book you will discover the techniques, recipes and skills with XGBoost that you can then bring to your own machine learning projects. Gradient Boosting does have a some fascinating math under the covers, but you do not need to know it to be able to pick it up as a tool and wield it on important projects to deliver real value. From the applied perspective, gradient boosting is quite a shallow field and a motivated developer can quickly pick it up and start making very real and impactful contributions.

xgboost简易安装，适合win10（64位），py64，出于对技术的热爱，资源来自公众号datadw

xgboost训练数据，Mushroom Classification。Mushroom Classification--xgboost训练数据

本人通过亲自实践，教大家一步步在win下安装xgboost(http://blog.csdn.net/jingyi130705008/article/details/71435562)，这个是之前的xgboost的C++版本，是在python使用xgboost之前必须的包。

由于xgboost的作者在github上删除了xgboost在windows系统下的目录文件，所以导致大家无法安装xgboost。本人通过亲自实践，教大家一步步在win下安装xgboost，这个是之前的xgboost的C++版本，是在python使用xgboost之前必须的包。