Gene expression programming classifier with concept drift detection based on fisher exact test

Joanna Jędrzejowicz , Piotr Jędrzejowicz

Abstract

The 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.
Author Joanna Jędrzejowicz (FMPI / II)
Joanna Jędrzejowicz,,
- Institute of Informatics
, Piotr Jędrzejowicz
Piotr Jędrzejowicz,,
-
Pages203-211
Publication size in sheets0.5
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 EnglishConcept drift, drift detection, gene expression programming, fisher exact test
ASJC Classification1700 General Computer Science; 1800 General Decision Sciences
DOIDOI:10.1007/978-981-13-8311-3_18
Languageen angielski
File
IDT 2019PJ_1566148458.pdf 2.65 MB
Score (nominal)20
Score sourcepublisherList
ScoreMinisterial score = 20.0, 28-01-2020, ChapterFromConference
Publication indicators Scopus SNIP (Source Normalised Impact per Paper): 2018 = 0.337
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