Jose M. Barrera , Alejandro Reina-Reina , Ana Lavalle , Alejandro Maté , Juan Trujillo
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引用次数: 0
Abstract
The rise of Artificial Intelligence (AI) and Deep Learning has led to Machine Learning (ML) becoming a common practice in academia and enterprise. However, a successful ML project requires deep domain knowledge as well as expertise in a plethora of algorithms and data processing techniques. This leads to a stronger dependency and need for communication between developers and stakeholders where numerous requirements come into play. More specifically, in addition to functional requirements such as the output of the model (e.g. classification, clustering or regression), ML projects need to pay special attention to a number of non-functional and quality aspects particular to ML. These include explainability, noise robustness or equity among others. Failure to identify and consider these aspects will lead to inadequate algorithm selection and the failure of the project. In this sense, capturing ML requirements becomes critical. Unfortunately, there is currently an absence of ML requirements modeling approaches. Therefore, in this paper we present the first i* extension for capturing ML requirements and apply it to two real-world projects. Our study covers two main objectives for ML requirements: (i) allows domain experts to specify objectives and quality aspects to be met by the ML solution, and (ii) facilitates the selection and justification of the most adequate ML approaches. Our case studies show that our work enables better ML algorithm selection, preprocessing implementation tailored to each algorithm, and aids in identifying missing data. In addition, they also demonstrate the flexibility of our study to adapt to different domains.
期刊介绍:
The quality of software, well-defined interfaces (hardware and software), the process of digitalisation, and accepted standards in these fields are essential for building and exploiting complex computing, communication, multimedia and measuring systems. Standards can simplify the design and construction of individual hardware and software components and help to ensure satisfactory interworking.
Computer Standards & Interfaces is an international journal dealing specifically with these topics.
The journal
• Provides information about activities and progress on the definition of computer standards, software quality, interfaces and methods, at national, European and international levels
• Publishes critical comments on standards and standards activities
• Disseminates user''s experiences and case studies in the application and exploitation of established or emerging standards, interfaces and methods
• Offers a forum for discussion on actual projects, standards, interfaces and methods by recognised experts
• Stimulates relevant research by providing a specialised refereed medium.