Estimating text regressions using txtreg_train

IF 3.2 2区 数学 Q1 SOCIAL SCIENCES, MATHEMATICAL METHODS
Carlo Schwarz
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引用次数: 0

Abstract

In this article, I introduce new commands to estimate text regressions for continuous, binary, and categorical variables based on text strings. The command txtreg_train automatically handles text cleaning, tokenization, model training, and cross-validation for lasso, ridge, elastic-net, and regularized logistic regressions. The txtreg_predict command obtains the predictions from the trained text regression model. Furthermore, the txtreg_analyze command facilitates the analysis of the coefficients of the text regression model. Together, these commands provide a convenient toolbox for researchers to train text regressions. They also allow sharing of pretrained text regression models with other researchers.
使用txtreg_train估计文本回归
在本文中,我将介绍一些新的命令,用于基于文本字符串估计连续变量、二进制变量和分类变量的文本回归。命令txtreg_train自动处理lasso、ridge、elastic-net和正则化逻辑回归的文本清理、标记化、模型训练和交叉验证。txtreg_predict命令从经过训练的文本回归模型中获得预测结果。此外,txtreg_analyze命令有助于分析文本回归模型的系数。总之,这些命令为研究人员提供了一个方便的工具箱来训练文本回归。它们还允许与其他研究人员共享预训练的文本回归模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Stata Journal
Stata Journal 数学-统计学与概率论
CiteScore
7.80
自引率
4.20%
发文量
44
审稿时长
>12 weeks
期刊介绍: The Stata Journal is a quarterly publication containing articles about statistics, data analysis, teaching methods, and effective use of Stata''s language. The Stata Journal publishes reviewed papers together with shorter notes and comments, regular columns, book reviews, and other material of interest to researchers applying statistics in a variety of disciplines.
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