Adaptive sampling for active learning with genetic programming

Active learning is a machine learning paradigm allowing to decide which inputs to use for training. It is introduced to Genetic Programming (GP) essentially thanks to the dynamic data sampling, used to address some known issues such as the computational cost, the over-fitting problem and the imbalan...

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Vydáno v:	Cognitive systems research Ročník 65; s. 23 - 39
Hlavní autoři:	Ben Hamida, Sana, Hmida, Hmida, Borgi, Amel, Rukoz, Marta
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier B.V 01.01.2021 Elsevier
Témata:	Active learning Adaptive sampling Computer Science Genetic programming Machine learning Sampling frequency control Training data sampling Training data sampling Adaptive sampling Active learning Genetic programming Sampling frequency control Machine learning
ISSN:	1389-0417, 1389-0417
On-line přístup:	Získat plný text
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