Implementing machine learning in an enterprise involves tackling a wide range of complexities with respect to requirements elicitation, design, development, and deployment of such solutions. Despite the necessity and relevance of requirements engineering approaches to the process, not much research has been done in this area. This paper employs a case study method to evaluate the expressiveness and usefulness of GR4ML, a conceptual modeling framework for requirements elicitation, design, and development of machine learning solutions. Our results confirm that the framework includes an adequate set of concepts for expressing machine learning requirements and solution design. The case study also demonstrates that the framework can be useful in machine learning projects by revealing new requirements that would have been missed without using the framework, as well as, by facilitating communication among project team members of different roles and backgrounds. Feedback from study participants and areas of improvement to the framework are also discussed.

中文翻译：

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从三个角度对机器学习需求建模：来自医疗保健领域的案例报告

在企业中实施机器学习涉及解决与此类解决方案的需求获取、设计、开发和部署相关的广泛复杂性。尽管需求工程方法对流程具有必要性和相关性，但在这方面的研究并不多。本文采用案例研究方法来评估 GR4ML 的表达能力和实用性，GR4ML 是一种用于机器学习解决方案的需求获取、设计和开发的概念建模框架。我们的结果证实，该框架包含一套足够的概念来表达机器学习要求和解决方案设计。该案例研究还表明，该框架可以通过揭示在不使用该框架的情况下会遗漏的新需求，以及促进不同角色和背景的项目团队成员之间的交流，从而在机器学习项目中发挥作用。还讨论了研究参与者的反馈以及对框架的改进领域。