Post deployment recycling of machine learning models

IF 3.5 2区计算机科学 Q1 COMPUTER SCIENCE, SOFTWARE ENGINEERING

Empirical Software Engineering Pub Date : 2024-06-15 DOI:10.1007/s10664-024-10492-2

Harsh Patel, Bram Adams, Ahmed E. Hassan

引用次数: 0

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机器学习模型部署后的再循环

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

Empirical Software Engineering 工程技术-计算机：软件工程

CiteScore

8.50

自引率

12.20%

发文量

169

审稿时长

>12 weeks

期刊介绍： Empirical Software Engineering provides a forum for applied software engineering research with a strong empirical component, and a venue for publishing empirical results relevant to both researchers and practitioners. Empirical studies presented here usually involve the collection and analysis of data and experience that can be used to characterize, evaluate and reveal relationships between software development deliverables, practices, and technologies. Over time, it is expected that such empirical results will form a body of knowledge leading to widely accepted and well-formed theories. The journal also offers industrial experience reports detailing the application of software technologies - processes, methods, or tools - and their effectiveness in industrial settings. Empirical Software Engineering promotes the publication of industry-relevant research, to address the significant gap between research and practice.