Concept Drift Detection via Equal Intensity k-Means Space Partitioning

The data stream poses additional challenges to statistical classification tasks because distributions of the training and target samples may differ as time passes. Such a distribution change in streaming data is called concept drift. Numerous histogram-based distribution change detection methods hav...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE transactions on cybernetics Jg. 51; H. 6; S. 3198 - 3211
Hauptverfasser:	Liu, Anjin, Lu, Jie, Zhang, Guangquan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.06.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Centroids Change detection Change detection algorithms Chi-square test Clustering algorithms Clusters Concept drift data stream Data transmission Detection algorithms Drift Greedy algorithms Heuristic algorithms Heuristic methods Histograms multivariate two-sample test Partitioning Partitioning algorithms Sensitivity space partition Statistical methods Statistical tests Training
ISSN:	2168-2267, 2168-2275, 2168-2275
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!