S Arora, R Rani, N Saxena - Wiley Interdisciplinary Reviews …, 2024 - Wiley Online Library
Last decade demonstrate the massive growth in organizational data which keeps on increasing multi‐fold as millions of records get updated every second. Handling such vast …
P Sidhu, MPS Bhatia - International Journal of Intelligent Systems …, 2015 - mecs-press.org
Various types of online learning algorithms have been developed so far to handle concept drift in data streams. We perform more detailed evaluation of these algorithms through new …
B Feng, Y Gu, H Yu, X Yang, S Gao - IEEE Access, 2022 - ieeexplore.ieee.org
This study proposes a novel incremental learning algorithm called distribution matching ensemble (DME) in context of adaptive weighted ensemble learning. In particular, DME …
U Ali, T Mahmood - International Journal of Machine Learning and …, 2024 - Springer
In streaming data environments, data characteristics and probability distributions are likely to change over time, causing a phenomenon called concept drift, which poses challenges for …
The term concept drift refers to the change of distribution underlying the data. It is an inherent property of evolving data streams. Concept drift detection and adaptation has been …
Learning in non-stationary environments remains challenging due to dynamic and unknown probability distribution. This issue is even more problematic when there is a lack of …
K Goel, S Batra - International Journal of Computational …, 2021 - inderscienceonline.com
In machine learning and predictive analytics, the underlying data distributions tend to change with the course of time known as concept drift. Accurate labelling in case of …
GJ Aguiar, A Cano - Knowledge-Based Systems, 2024 - Elsevier
Adapting to drifting data streams is a significant challenge in online learning. Concept drift must be detected for effective model adaptation to evolving data properties. Concept drift …
In increasing number of real world applications, data are presented as streams that may evolve over time and this is known by concept drift. Handling concept drift through ensemble …