Research about pruning hyper-parameter optimization method based on transfer learning in geographic information system

Recently, researchers have found that some automated optimization methods and techniques can speed up the whole search process and can obtain better model hyper-parameter configurations. In this paper, the optimized initial hyper-parameter configuration is obtained through the loss function defined...

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Vydáno v:	Arabian journal of geosciences Ročník 14; číslo 5
Hlavní autoři:	Zhang, Xiaohang, Li, Yuqi, Li, Zhengren
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Cham Springer International Publishing 01.03.2021 Springer Nature B.V
Témata:	Algorithms Configurations Design optimization Design parameters Earth and Environmental Science Earth science Earth Sciences Geographic information systems Geographical information systems Geological Modeling and Geospatial Data Analysis Gmgda 2019 Information systems Machine learning Mathematical models Optimization Parameters Remote sensing Search process Transfer learning Geographic information system (GIS) Hyper-parameter optimization Automated machine learning algorithm Pruning strategy Transfer learning SMBO model
ISSN:	1866-7511, 1866-7538
On-line přístup:	Získat plný text
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