Loading...

SELM: Software engineering of machine learning models

Jafari, N ; Sharif University of Technology | 2021

418 Viewed
  1. Type of Document: Article
  2. DOI: 10.3233/FAIA210007
  3. Publisher: IOS Press BV , 2021
  4. Abstract:
  5. One of the pillars of any machine learning model is its concepts. Using software engineering, we can engineer these concepts and then develop and expand them. In this article, we present a SELM framework for Software Engineering of machine Learning Models. We then evaluate this framework through a case study. Using the SELM framework, we can improve a machine learning process efficiency and provide more accuracy in learning with less processing hardware resources and a smaller training dataset. This issue highlights the importance of an interdisciplinary approach to machine learning. Therefore, in this article, we have provided interdisciplinary teams' proposals for machine learning. © 2021 The authors and IOS Press. All rights reserved
  6. Keywords:
  7. Efficiency ; Engineering education ; Machine learning ; Case-studies ; Engineering methodology ; Hardware resources ; IMPROVE-A ; Learning efficiency ; Machine learning models ; Process efficiency ; Processing hardware ; Small training ; Training dataset ; Software engineering
  8. Source: 20th International Conference on New Trends in Intelligent Software Methodologies, Tools and Techniques, SoMeT 2021, 21 September 2021 through 23 September 2021 ; Volume 337 , 2021 , Pages 48-54 ; 09226389 (ISSN); 9781643681948 (ISBN)
  9. URL: https://ebooks.iospress.nl/doi/10.3233/FAIA210007