ORCID: https://orcid.org/0000-0001-9954-462X; Tornede, Alexander
ORCID: https://orcid.org/0000-0002-2415-2186; Fehring, Lukas
ORCID: https://orcid.org/0000-0001-8057-4650; Gehring, Lukas; Graf, Helena
ORCID: https://orcid.org/0000-0001-9447-0609; Hanselle, Jonas
ORCID: https://orcid.org/0000-0002-1231-4985; Mohr, Felix
ORCID: https://orcid.org/0000-0002-9293-2424 und Wever, Marcel
ORCID: https://orcid.org/0000-0001-9782-6818
(20. April 2023):
PyExperimenter: Easily distribute experiments and track results.
In: Journal of Open Source Software, Vol. 8, No. 84: p. 5149
[PDF, 236kB]

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.
Item Type: | Journal article |
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Faculties: | Mathematics, Computer Science and Statistics > Computer Science > Artificial Intelligence and Machine Learning |
Subjects: | 000 Computer science, information and general works > 000 Computer science, knowledge, and systems |
URN: | urn:nbn:de:bvb:19-epub-107521-2 |
ISSN: | 2475-9066 |
Language: | English |
Item ID: | 107521 |
Date Deposited: | 01. Nov 2023 16:54 |
Last Modified: | 11. Oct 2024 13:41 |
DFG: | Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 160364472 |