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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Bibliographic Details

Published in:	Cognitive systems research Vol. 65; pp. 23 - 39
Main Authors:	Ben Hamida, Sana, Hmida, Hmida, Borgi, Amel, Rukoz, Marta
Format:	Journal Article
Language:	English
Published:	Elsevier B.V 01.01.2021 Elsevier
Subjects:	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
Online Access:	Get full text
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