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Title: GitHub - frank19-lab/TimeSeriesPrediction: 天池智慧交通预测挑战赛解决方案 · GitHub

Open Graph Title: GitHub - frank19-lab/TimeSeriesPrediction: 天池智慧交通预测挑战赛解决方案

X Title: GitHub - frank19-lab/TimeSeriesPrediction: 天池智慧交通预测挑战赛解决方案

Description: 天池智慧交通预测挑战赛解决方案. Contribute to frank19-lab/TimeSeriesPrediction development by creating an account on GitHub.

Open Graph Description: 天池智慧交通预测挑战赛解决方案. Contribute to frank19-lab/TimeSeriesPrediction development by creating an account on GitHub.

X Description: 天池智慧交通预测挑战赛解决方案. Contribute to frank19-lab/TimeSeriesPrediction development by creating an account on GitHub.

Opengraph URL: https://github.com/frank19-lab/TimeSeriesPrediction

X: @github

direct link

Domain: github.com

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frank19-lab	https://github.com/frank19-lab
TimeSeriesPrediction	https://github.com/frank19-lab/TimeSeriesPrediction
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6 Commits	https://github.com/frank19-lab/TimeSeriesPrediction/commits/master/
	https://github.com/frank19-lab/TimeSeriesPrediction/commits/master/
README.md	https://github.com/frank19-lab/TimeSeriesPrediction/blob/master/README.md
README.md	https://github.com/frank19-lab/TimeSeriesPrediction/blob/master/README.md
preprocess.py	https://github.com/frank19-lab/TimeSeriesPrediction/blob/master/preprocess.py
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README	https://github.com/frank19-lab/TimeSeriesPrediction
	https://github.com/frank19-lab/TimeSeriesPrediction#天池智慧交通预测挑战赛解决方案
Github	https://github.com/PENGZhaoqing/TimeSeriesPrediction
	https://github.com/frank19-lab/TimeSeriesPrediction#1-数据和题目说明
	https://github.com/frank19-lab/TimeSeriesPrediction#2-题目分析和思路
	https://github.com/frank19-lab/TimeSeriesPrediction#3-数据分析
	https://github.com/frank19-lab/TimeSeriesPrediction#31-特征变换
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	https://github.com/frank19-lab/TimeSeriesPrediction#32-数据平滑
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	https://github.com/frank19-lab/TimeSeriesPrediction#33-缺失值补全
	https://github.com/frank19-lab/TimeSeriesPrediction#331-为什么要补全缺失值-不补全可不可以
	https://github.com/frank19-lab/TimeSeriesPrediction#332-缺失值补全的方法
	https://github.com/frank19-lab/TimeSeriesPrediction#333-准备工作找到缺失值
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	https://github.com/frank19-lab/TimeSeriesPrediction#334-补全步骤seasonal-date-trend-daily-hour-trend--xgboost-predict
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	https://github.com/frank19-lab/TimeSeriesPrediction#34-分析提取特征
	https://github.com/frank19-lab/TimeSeriesPrediction#341-与路相关的特征
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这里	https://xgboost.readthedocs.io/en/latest/R-package/discoverYourData.html
这里	https://stackoverflow.com/questions/24715230/can-sklearn-random-forest-directly-handle-categorical-features
这里	http://www.kdnuggets.com/2015/12/beyond-one-hot-exploration-categorical-variables.html
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	https://github.com/frank19-lab/TimeSeriesPrediction#342-与时间相关的特征
	https://camo.githubusercontent.com/bee64fcdd40ff3de68162ab3fdf379f307841bcb6fdd45bac94063672889b33b/687474703a2f2f696d672e626c6f672e6373646e2e6e65742f32303137303931353135333530363838353f77617465726d61726b2f322f746578742f6148523063446f764c324a736232637559334e6b626935755a585176634842774f444d774d4467344e513d3d2f666f6e742f3561364c354c32542f666f6e7473697a652f3430302f66696c6c2f49304a42516b46434d413d3d2f646973736f6c76652f37302f677261766974792f536f75746845617374
	https://camo.githubusercontent.com/cefc63af0cbc2dc08518527157ce040385340ad7067ec57e5303d44fac6e8705/687474703a2f2f696d672e626c6f672e6373646e2e6e65742f32303137303931353135353331313039343f77617465726d61726b2f322f746578742f6148523063446f764c324a736232637559334e6b626935755a585176634842774f444d774d4467344e513d3d2f666f6e742f3561364c354c32542f666f6e7473697a652f3430302f66696c6c2f49304a42516b46434d413d3d2f646973736f6c76652f37302f677261766974792f536f75746845617374
	https://github.com/frank19-lab/TimeSeriesPrediction#4-训练模模型和cross-valid
这里	https://stats.stackexchange.com/questions/14099/using-k-fold-cross-validation-for-time-series-model-selection
这里	https://github.com/PENGZhaoqing/TimeSeriesPrediction/blob/master/xgbosst.py
	https://camo.githubusercontent.com/cd1035575ea71546084b2e9b3677e98f6b5f5d130773523a9be2a9935abf6f44/687474703a2f2f696d672e626c6f672e6373646e2e6e65742f32303137303931353230353034343634303f77617465726d61726b2f322f746578742f6148523063446f764c324a736232637559334e6b626935755a585176634842774f444d774d4467344e513d3d2f666f6e742f3561364c354c32542f666f6e7473697a652f3430302f66696c6c2f49304a42516b46434d413d3d2f646973736f6c76652f37302f677261766974792f536f75746845617374
	https://github.com/frank19-lab/TimeSeriesPrediction#5-总结
blog.csdn.net/ppp8300885/article/details/77934822	http://blog.csdn.net/ppp8300885/article/details/77934822
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