CONDA-PM—a systematic review and framework for concept drift analysis in process mining
- Standort
-
Deutsche Nationalbibliothek Frankfurt am Main
- Umfang
-
Online-Ressource
- Sprache
-
Englisch
- Erschienen in
-
In: Algorithms ; 13 (2020). - Art.-Nr. 161. - eISSN 1999-4893
- Ereignis
-
Veröffentlichung
- (wo)
-
Ulm
- (wer)
-
Universität Ulm
- (wann)
-
2020
- Urheber
-
Elkhawaga, Ghada
Abuelkheir, Mervat
Barakat, Sherif I.
Riad, Alaa M.
Reichert, Manfred
- DOI
-
10.18725/OPARU-33855
- URN
-
urn:nbn:de:bsz:289-oparu-33917-2
- Rechteinformation
-
Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Letzte Aktualisierung
-
15.08.2025, 07:25 MESZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Deutsche Nationalbibliothek. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Beteiligte
- Elkhawaga, Ghada
- Abuelkheir, Mervat
- Barakat, Sherif I.
- Riad, Alaa M.
- Reichert, Manfred
- Universität Ulm
Entstanden
- 2020
Ähnliche Objekte (12)
Scalable concept drift adaptation for stream data mining
Data stream mining: methods and challenges for handling concept drift
Supervised learning in the presence of concept drift: a modelling framework
Handling concept drift in adaptive information systems
Approaching Concept Drift by Context Feature Partitioning
Online Diskriminanzanalyse für Datensituationen mit Concept Drift
Concept drift detection and adaptation for machine learning
Deep learning framework for handling concept drift and class imbalanced complex decision-making on streaming data
Rahmenkonzept. [framework concept]
Multi-type concept drift detection under a dual-layer variable sliding window in frequent pattern mining with cloud computing
Concept and development of enhanced lateral drift (ELAD) Sensors
Concept Drift and Adaptation for Emotion Detection in Twitter
Scalable concept drift adaptation for stream data mining
Data stream mining: methods and challenges for handling concept drift
Supervised learning in the presence of concept drift: a modelling framework
Handling concept drift in adaptive information systems
Approaching Concept Drift by Context Feature Partitioning
Online Diskriminanzanalyse für Datensituationen mit Concept Drift
Concept drift detection and adaptation for machine learning
Deep learning framework for handling concept drift and class imbalanced complex decision-making on streaming data
Rahmenkonzept. [framework concept]
Multi-type concept drift detection under a dual-layer variable sliding window in frequent pattern mining with cloud computing
Concept and development of enhanced lateral drift (ELAD) Sensors
Concept Drift and Adaptation for Emotion Detection in Twitter
Scalable concept drift adaptation for stream data mining
Data stream mining: methods and challenges for handling concept drift
Supervised learning in the presence of concept drift: a modelling framework
Handling concept drift in adaptive information systems
Approaching Concept Drift by Context Feature Partitioning
Online Diskriminanzanalyse für Datensituationen mit Concept Drift
Concept drift detection and adaptation for machine learning
Deep learning framework for handling concept drift and class imbalanced complex decision-making on streaming data
Rahmenkonzept. [framework concept]
Multi-type concept drift detection under a dual-layer variable sliding window in frequent pattern mining with cloud computing
Concept and development of enhanced lateral drift (ELAD) Sensors