历史人,程序猿。
🔭 I’m currently working on and learning:
- NLP
- DL
马上消费金融挑战者大赛-违约用户风险预测--第三名方案
您好!我是一名在读学生,因为拜读并学习了您团队的关于这个赛题的解决方案,收益很大,十分感谢,但是您上传的关于马上金融的项目中关于特征提取部分没有上传完整(缺少文件feature_order_info_dealed.csv文件的生成部分)因为自己是新手,很希望能够完整学习下来,不知是不是因为不方便公开还是别的原因,所以想向您请教问一下。再次十分感谢您的开源,期待您的回复。谢谢!
看了您的ppt,有以下问题
您的意思是指缺失所在的列,没缺失的转为1,缺失的转为0,然后统计样本中0的个数,再除以用户信息表的总维度如何理解(用户信息的数据总数)?那么请问相除后,构造的评估用户资料完整度的特征有何作用?
问题2:尝试将身份信息和时间信息转化为可以入模的变量怎么实现?
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