This project forked from kongdzh/2017-jdd-global-data-explorer-competition
2017京东金融全球数据探索者大赛(3rd place)
本次大赛一共有四个赛题，我做的的是登录行为识别赛题。成绩为A榜第一，B榜第三。
团队名称：jd_156192rqk。
成员分别来自西安电子科技大学(队友)和四川大学(我)。
pandas
numpy
sklearn
xgboost
python2.7
程序入口：sh run.sh
登录行为识别赛题主要是根据登录行为来判断本次交易是否是危险交易。我们的方案主要是通过刻画id画像、ip画像和dev画像的思路来构造特征，然后分别用xgboost、LR来预测， 取两个模型中风险最大的top200，对这200个进行交集运算。对于某次交易，如果xgboost和LR模型同时预测为危险交易，则判定该次交易为危险交易；否则为正常交易。特征构造 可参见代码，里面有详细的注释。
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