Active broad learning with multi-objective evolution for data stream classification
Active broad learning with multi-objective evolution for data stream classification
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Publisher
Cham: Springer International Publishing
Journal title
Language
English
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Publisher
Cham: Springer International Publishing
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Scope and Contents
Contents
In a streaming environment, the characteristics and labels of instances may change over time, forming concept drifts. Previous studies on data stream learning generally assume that the true label of each instance is available or easily obtained, which is impractical in many real-world applications due to expensive time and labor costs for labeling....
Alternative Titles
Full title
Active broad learning with multi-objective evolution for data stream classification
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Record Identifier
TN_cdi_doaj_primary_oai_doaj_org_article_e94ea7db92d04d17a1a3ed0983e941c3
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_e94ea7db92d04d17a1a3ed0983e941c3
Other Identifiers
ISSN
2199-4536
E-ISSN
2198-6053
DOI
10.1007/s40747-023-01154-9
