texttregress:一个Python包,用于对长格式文本数据进行高级回归分析

IF 1.3 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Jinhang Jiang , Ben Liu , Weiyao Peng , Karthik Srinivasan
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引用次数: 0

摘要

TextRegress是一个开源Python包,它利用最先进的深度学习技术对长格式文本数据执行回归分析。与局限于分类、情感或可读性度量的传统文本挖掘工具不同,TextRegress提供了一个统一的框架,用于对连续结果进行预测建模。通过将先进的编码方法(包括基于变压器的嵌入、TF-IDF和预训练的hug Face模型)与健壮的PyTorch Lightning后端集成,TextRegress通过自动分块和动态特征集成有效地处理长文本。其灵活的体系结构和可定制的培训范例使不同领域的研究人员和实践者能够部署复杂的回归模型,促进文本分析的可重复性和加速创新。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
TextRegress: A Python package for advanced regression analysis on long-form text data
TextRegress is an open-source Python package that leverages state-of-the-art deep learning techniques to perform regression analysis on long-form text data. Departing from conventional text mining tools that are confined to classification, sentiment, or readability metrics, TextRegress provides a unified framework for conducting predictive modeling of continuous outcomes. By integrating advanced encoding methods – including transformer-based embeddings, TF-IDF, and pre-trained Hugging Face models – with a robust PyTorch Lightning backend, TextRegress efficiently processes long texts through automatic chunking and dynamic feature integration. Its flexible architecture and customizable training paradigms empower researchers and practitioners across diverse domains to deploy sophisticated regression models, fostering reproducibility and accelerating innovation in text analytics.
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来源期刊
Software Impacts
Software Impacts Software
CiteScore
2.70
自引率
9.50%
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0
审稿时长
16 days
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