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...

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Vydané v:	IEEE transactions on cybernetics Ročník 51; číslo 6; s. 3198 - 3211
Hlavní autori:	Liu, Anjin, Lu, Jie, Zhang, Guangquan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	United States IEEE 01.06.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	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
On-line prístup:	Získať plný text
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