Online Passive-Aggressive Multilabel Classification Algorithms

Most existing multilabel classification methods are batch learning methods, which may suffer from expensive retraining costs when dealing with new incoming data. In order to overcome the drawbacks of batch learning, we develop a family of online multilabel classification algorithms, which can update...

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Veröffentlicht in:	IEEE transaction on neural networks and learning systems Jg. 34; H. 12; S. 10116 - 10129
Hauptverfasser:	Zhai, Tingting, Wang, Hao
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.12.2023 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Classification Correlation Data models Distance learning Electronic learning Internet Labeling Labels Learning Learning systems Machine learning Multilabel learning online learning online multilabel classification Optimization passive-aggressive (PA) learning Prediction algorithms Prediction models Predictive models Task analysis
ISSN:	2162-237X, 2162-2388, 2162-2388
Online-Zugang:	Volltext
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