Model Reports, a Supervision Tool for Machine Learning Engineers and Users
2022 ◽
Vol 16
◽
pp. 50-54
Keyword(s):
This article investigates a methodology to design an automated supervision report, ensuring the suitability between the designers and the users of an algorithm. For this purpose, we built a super-vision tool, focused on error diagnosis. The argumentation of the article relies first on the exposition of the reasons to use model reports as a supervision artefact, with a prototype of implementation at an organization level, describing the necessary tooling to industrialize its production. Finally, we propose a method for supervising machine learning algorithms in a responsible and sustainable way, starting from the conception of the algorithm, along its development and dur-ing its operating phase.
Keyword(s):
2019 ◽
Vol 1
(2)
◽
pp. 78-80
Keyword(s):
2017 ◽
Vol 12
(1)
◽
pp. 21
◽
Keyword(s):
Keyword(s):
Keyword(s):
2017 ◽
Vol 5
(9)
◽