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[HTML][HTML] Concept drift detection in data stream mining: A literature review
S Agrahari, AK Singh - Journal of King Saud University-Computer and …, 2022 - Elsevier
In recent years, the availability of time series streaming information has been growing
enormously. Learning from real-time data has been receiving increasingly more attention …
enormously. Learning from real-time data has been receiving increasingly more attention …
Concept drift adaptation methods under the deep learning framework: A literature review
Q ** of streaming data
Online learning is a complex task, especially when the data stream changes its distribution
over time. It's challenging to monitor and detect these changes to maintain the performance …
over time. It's challenging to monitor and detect these changes to maintain the performance …
Dynamic classification ensembles for handling imbalanced multiclass drifted data streams
Abstract Machine learning models often encounter significant difficulties when dealing with
multiclass imbalanced data streams in nonstationary environments. These challenges can …
multiclass imbalanced data streams in nonstationary environments. These challenges can …
A multi-level weighted concept drift detection method
Z Chen, M Han, H Wu, M Li, X Zhang - The Journal of Supercomputing, 2023 - Springer
The concept drift detection method is an online learner. Its main task is to determine the
position of drifts in the data stream, so as to reset the classifier after detecting the drift to …
position of drifts in the data stream, so as to reset the classifier after detecting the drift to …