Details zu Publikationen

PyExperimenter

Easily distribute experiments and track results

verfasst von
Tanja Tornede, Alexander Tornede, Lukas Fehring, Lukas Gehring, Helena Graf, Jonas Hanselle, Felix Mohr, Marcel Wever
Abstract

PyExperimenter is a tool to facilitate the setup, documentation, execution, and subsequent evaluation of results from an empirical study of algorithms and in particular is designed to reduce the involved manual effort significantly. It is intended to be used by researchers in the field of artificial intelligence, but is not limited to those.

Organisationseinheit(en)
Fachgebiet Maschinelles Lernen
Externe Organisation(en)
Universität Paderborn
Ludwig-Maximilians-Universität München (LMU)
Typ
Artikel
Journal
Journal of Open Source Software
Anzahl der Seiten
3
Publikationsdatum
20.04.2023
Publikationsstatus
Veröffentlicht
Peer-reviewed
Ja
Elektronische Version(en)
https://doi.org/10.21105/joss.05149 (Zugang: Offen)