xgboost GitHub 源码包下载，解压 https://github.com/dmlc/xgboost 下载xgboost.dll 将xgboost.dll放到解压后的\xgboost-master\python-package\xgboost目录中 进入\xgboost-master\python-package， 执行 python setup.py install

面向康复工程的脑电信号分析和判别模型，脑电信号；随机森林；特征选择；XGBoost ，解决了四个问题，有详细的方法叙述和结果，可供参考

特征工程和xgboost调优案例，面向初学xgboost以及想要进阶学习xgboost调参的程序猿

xgboost模型whl安装包

XGBoost 分类模型的Python实现-附件资源

作者是在windows10，64位，python3.7.0，Anaconda 3环境下进行安装的。附有安装教程。

xgboost-0.82-py2.py3-none-win_amd64.whl

陈天奇xgb论文。Tree boosting is a highly eective and widely used machine learning method. In this paper, we describe a scalable endto- end tree boosting system called XGBoost, which is used widely by data scientists to achieve state-of-the-art results on many machine learning challenges. We propose a novel sparsity-aware algorithm for sparse data and weighted quantile sketch for approximate tree learning. More importantly, we provide insights on cache access patterns, data compression and sharding to build a scalable tree boosting system. By combining these insights, XGBoost scales beyond billions of examples using far fewer resources than existing systems.

Allstate Claims Severity data

二分类数据集，乳腺癌数据集，568条记录，30类特征，可以用分类算法如xgboost，svm等分类算法