Automated-Essay-Grader:该存储库包含为 CSCI-GA.2590-001 自然语言处理 15Spring 的最终项目编写的所有代码-源码

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自动论文评分器 该存储库包含为 CSCI-GA.2590-001 自然语言处理 15Spring 的最终项目编写的所有代码 团队成员: 禹城路 孙芳云 刘文英 我们的项目基于这里的 Kaggle 比赛: ://www.kaggle.com/c/asap-aes 跑步: 首先,您需要安装requirements.txt 中的所有包。 然后,使用 python run.py 运行整个程序。 并且程序会首先生成所有需要的特征并将它们存储到 FeatureData 目录中,然后将这些特征添加到训练数据和测试数据中。 程序会将训练数据存入 TrainingData 目录,将测试数据存入 TestData 目录。 该过程大约需要 4-5 个小时。 最后,程序将训练线性回归模型、梯度提升树模型和随机森林回归模型,并将结果存储在 Result 目录中。 提醒: 由于线性回归在高维数据集中表

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