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2018_diantou_PhotovoltaicPowerStation

电投_光伏电站人工智能运维大数据处理分析：比赛链接

依赖库

  • numpy
  • pandas
  • sklearn
  • lightgbm
  • xgboost

项目结构

  • data : 数据存放地址
    • public.test.csv ：测试数据
    • public.train.csv : 训练数据
    • submit_example.csv : 提交样本
  • history_code_please_ignore : 比赛的时候的代码，请忽略这个文件
  • pictures : readme的source picture
  • result : 历史提交结果的submit文件
  • code.ipynb : 代码文件

团队成员：
@jlinbb
@wanlida
@ouc16020021031
@Troysps

最好的版本

location score rank detail
McDonald/McDonald_v4.ipynb 0.84609425068 30 一个完整的版本1.数据预处理 2.第一层xgboost gbdt rf lgbm knn 五个模型融合 3.第二层模型融合选择SVR
code_version_save/wan_8月4号22点11分.ipynb 0.84751743 22 增加一个强特 历史平均功率，knn模型不太好，选择xgboost gbdt rf lgbm四个模型，测试过单独增加列 用ID%205 没有效果，分数反而降低至0.846
code_version_save/wan_8月16号 0.84770610000.ipynb 0.84770610000 * 增加四列 历史平均功率 历史功率A 历史功率B 历史功率C

比赛的详细细节 detail_1.png

image
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a榜排名

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b榜排名

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备注

保密工作没有做好，很多队伍在github上检索到了我们的代码，已知的某队伍，部分使用我们的代码最终B榜11名
需要在github上使用英文书写相关信息
对于特征处理方面没有做好，暴力特征+特征选择 初赛A榜预计能到 前10
A榜过拟合比较严重

向大佬咨询的强特

他给我发的catboost的训练记录表 image

XX选用的模型是 xgboost gbdt catboost lgbm，我也试了试catboost 感觉使用很不熟练，a榜分数也不高，主要是catboost ；类别型特征需要特殊处理

image

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2018_diantou_photovoltaicpowerstation's People

Contributors

jlinbb avatar wanlida avatar

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