Zobrazeno 1 - 10
of 98
pro vyhledávání: '"Lee, Suhwan"'
Predictive Process Monitoring aims to forecast the future progress of process instances using historical event data. As predictive process monitoring is increasingly applied in online settings to enable timely interventions, evaluating the performanc
Externí odkaz:
http://arxiv.org/abs/2310.09000
Anomaly detection in process mining focuses on identifying anomalous cases or events in process executions. The resulting diagnostics are used to provide measures to prevent fraudulent behavior, as well as to derive recommendations for improving proc
Externí odkaz:
http://arxiv.org/abs/2203.09619
Autor:
Rizzi, Williams, Comuzzi, Marco, Di Francescomarino, Chiara, Ghidini, Chiara, Lee, Suhwan, Maggi, Fabrizio Maria, Nolte, Alexander
Explainability is motivated by the lack of transparency of black-box Machine Learning approaches, which do not foster trust and acceptance of Machine Learning algorithms. This also happens in the Predictive Process Monitoring field, where predictions
Externí odkaz:
http://arxiv.org/abs/2202.07760
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Publikováno v:
In Applied Thermal Engineering 25 January 2023 219 Part B
Publikováno v:
In International Journal of Refrigeration October 2021 130:76-86
Publikováno v:
In Expert Systems With Applications 1 October 2019 131:132-147
Publikováno v:
In Ophthalmology Retina August 2019 3(8):681-689
Autor:
Lee, Suhwan1 (AUTHOR) s.lee@uu.nl, Comuzzi, Marco2 (AUTHOR) eekfskgus@unist.ac.kr, Kwon, Nahyun2 (AUTHOR)
Publikováno v:
Algorithms. Jun2022, Vol. 15 Issue 6, p187. 17p.
Publikováno v:
Journal of Coastal Research, 2016 Mar 01, 1307-1311.
Externí odkaz:
https://www.jstor.org/stable/43752475