xgboost代码回归matlab-CS229_Project:通过遥感CNN功能预测贫困

上传者: 38687199 | 上传时间: 2021-06-05 16:05:53 | 文件大小: 112.99MB | 文件类型: ZIP
xgboost代码回归matlab 通过遥感CNN功能预测贫困 入门 对于此项目,我们提供了使用遥感CNN功能进行贫困预测的研究。 通过从CNN提供的4096个特征中精心选择特征,我们训练了一个模型,该模型可以比使用夜灯强度更好地预测财富指数。 我们分两部分进行研究,即特征选择和模型训练。 我们使用基于相关性,基于套索的和正向搜索方法来选择特征。 我们使用线性回归,岭回归,Lasso回归和XGBoost来训练我们的模型并比较性能。 您可以使用我们提供的代码来完成此过程。 先决条件 使用MATLAB提供的内置函数来开发特征选择方法和基本回归模型。 “ all_countries_dhs.mat”是包含所有训练数据和训练集的文件。 要在Python中运行XGBoost代码和VAE代码,您需要: Python 2.7 正在安装 请参考上面的链接,了解如何安装依赖项。 对于MacOS,如果您在计算机上安装了pip,则可以执行以下操作: pip install xgboost pip install -U scikit-learn python -m pip install --user num

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