GEP-Based ensemble classifier with drift-detection

Joanna Jędrzejowicz , Piotr Jędrzejowicz

Abstract

The paper proposes a new ensemble classifier using Gene Expression Programming as the induction engine. The approach aims at predicting unknown class labels for datasets with concept drift. For constructing the proposed ensemble we use the two-level scheme where at the lower level base classifiers are induced and at the upper level, the meta-classifier is produced. The classification process is controlled by the well-known early drift detection mechanism. To validate the approach computational experiment has been carried out. Its results confirmed that the proposed classifier performs well.
Author Joanna Jędrzejowicz (FMPI / II)
Joanna Jędrzejowicz,,
- Institute of Informatics
, Piotr Jędrzejowicz
Piotr Jędrzejowicz,,
-
Pages121-131
Publication size in sheets0.5
Book Bramer Max, Petridis Miltos (eds.): Artificial Intelligence XXXV: 38th SGAI International Conference on Artificial Intelligence, AI 2018 Cambridge, UK, December 11-13, 2018: proceedings, Lecture Notes In Computer Science, no. 11311, 2018, Springer, ISBN 978-3-030-04190-8, [978-3-030-04191-5], 468 p., DOI:10.1007/978-3-030-04191-5_9
Keywords in Englishgene expression programming, classifier ensemble, datasets with concept drif
URL https://link.springer.com/content/pdf/10.1007%2F978-3-030-04191-5_9.pdf
Languageen angielski
Score (nominal)5
ScoreMinisterial score = 5.0, 29-11-2018, BookChapterNotSeriesMainLanguages
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