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buspassengerpredict's Introduction

#目录说明:

##source:

  • CheckTrainData.py:查看原始数据
  • DealTrainData.py:处理交易数据
  • DealWeatherData.py:处理天气数据
  • error.py:误差函数
  • ExploreTrainData.py:交易数据探索绘图
  • ExploreTrainWeather.py:交易数据关联天气数据探索绘图
  • predict.py:预测20141225-20141231的客流
  • TestDataResult.py:测试集生成
  • TrainDataResult.py:训练集生成
  • TrainModel.py:训练模型

##data: 由于大赛已经结束,咱们就把20141225-20141231的交易数据拿出来当作未知

  • date_holiday.txt:日期节假日、工作日数据
  • gd_line_desc.txt:比赛提供的公交线路信息数据
  • gd_train_data.txt:比赛提供的原始交易数据
  • gd_weather_report.txt:比赛提供的天气状况
  • line6_passenger_hour_test.csv:20141225-20141231线路6的客流
  • line11_passenger_hour_test.csv:20141225-20141231线路11的客流
  • train_data.csv:去掉20141225-20141231的交易数据
  • train_data_test.csv:20141225-20141231的交易数据,作为测试集

由于github对单个文件大小有限制,我把数据上传到了百度云盘 链接:https://pan.baidu.com/s/1vRsr_ur7fgtSz7GHzlALSw 密码:x1r4

##model: 存放训练好的模型

具体细节移步https://blog.csdn.net/u010606321/article/details/82501341

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