Gene expression programming classifier with concept drift detection based on fisher exact test
Joanna Jędrzejowicz , Piotr Jędrzejowicz
AbstractThe paper proposes to use gene expression programming with metagenes as a base classifier integrated with the Fisher exact test drift detector. The approach assumes maintaining during the classification process two windows, recent and older. If the drift is detected, the recent window is used to induce a new classifier with a view to adapt to the drift changes. The idea is validated in the computational experiment where the performance of the GEP-based classifier with Fisher exact test detector is compared with classifiers using Naïve Bayes and Hoeffding tree as the base learners.
|Publication size in sheets||0.5|
|Book||Czarnowski Ireneusz, Howlett Robert J. , Jain Lakhmi C. (eds.): Intelligent decision technologies 2019: proceedings of the 11th KES International Conference on Intelligent Decision Technologies (KES-IDT 2019), Smart Innovation, Systems and Technologies , vol. 1, no. 142, 2019, Springer, ISBN 978-981-13-8310-6, [978-981-13-8311-3], 377 p.|
|Keywords in English||Concept drift, drift detection, gene expression programming, fisher exact test|
|Score||= 20.0, 28-01-2020, ChapterFromConference|
|Publication indicators||: 2018 = 0.337|
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