Deep Forest Regression Based on Dynamic State Transition Optimization Algorithm

As a deep algorithm of non-neural network structure, deep forest regression (DFR) can be used to build soft measuring models of difficult-to-measure key parameters. However, as a kind of deep learning, the optimization of hyperparameters has become an inevitable problem in DFR. To solve above proble...

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Vydané v:	Chinese Automation Congress (Online) s. 3786 - 3791
Hlavní autori:	Xia, Heng, Tang, Jian, Qiao, Junfei
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 06.11.2020
Predmet:	Data models deep forest regression dynamic state transition algorithm Forestry Heuristic algorithms hyper-parameters optimization Optimization Stochastic processes Support vector machines Training
ISSN:	2688-0938
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