Broad Learning System Based on Maximum Correntropy Criterion

As an effective and efficient discriminative learning method, broad learning system (BLS) has received increasing attention due to its outstanding performance in various regression and classification problems. However, the standard BLS is derived under the minimum mean square error (MMSE) criterion,...

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Vydané v:	IEEE transaction on neural networks and learning systems Ročník 32; číslo 7; s. 3083 - 3097
Hlavní autori:	Zheng, Yunfei, Chen, Badong, Wang, Shiyuan, Wang, Weiqun
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.07.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Broad learning system (BLS) Classification Criteria incremental learning algorithms Learning algorithms Learning systems Machine learning maximum correntropy criterion (MCC) Mean square error methods Noise standards Optimization Outliers (statistics) Perturbation methods regression and classification Robustness Sensitivity enhancement Training
ISSN:	2162-237X, 2162-2388, 2162-2388
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