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2018年全国大学生计算机应用能力大赛之住房月租金预测第一名代码

License: Apache License 2.0

Jupyter Notebook 95.14% Python 4.86%

rental-prediction's Introduction

比赛页面

队伍成员:

@zywu2018

@QQ435248055

因个人原因,train.csv与test.csv均作过处理,与网站上提供的原数据不同;队友代码中所用数据也跟我的不同,运行代码时需要注意。

更改后的特征映射关系为:

原特征 更改后的特征
时间 Time
小区名 Neighborhood
小区房屋出租屋数量 RentRoom
楼层 Height
总层数 TolHeight
房屋面积 RoomArea
房屋朝向 RoomDir
居住状态 RentStatus
卧室数量 Bedroom
厅的数量 Livingroom
卫的数量 Bathroom
出租方式 RentType
Region
位置 BusLoc
地铁线路 SubwayLine
地铁站点 SubwaySta
距离 SubwayDis
装修情况 RemodCond
月租金 Rental

团队贡献:

@QQ435248055:可视化、XGB、统计规则

@zywu2018:LGB、CatBoost、结果融合

XGB: 1.94

LGB: 1.86

LGB+STA: 1.82

LGB+XGB+STA: 1.80

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